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Selection: with tag statistics [175 articles] 


Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure

Ecography, Vol. 40, No. 8. (1 August 2017), pp. 913-929,


Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic structure. Modern statistical approaches are increasingly accounting for such dependencies. However, when performing cross-validation, these structures are regularly ignored, resulting in serious underestimation of predictive error. One cause for the poor performance of uncorrected (random) cross-validation, noted often by modellers, are dependence structures in the data that persist as dependence structures in model residuals, violating the assumption of independence. Even more concerning, because often overlooked, is that structured data also ...


Statistical modeling: the two cultures (with comments and a rejoinder by the author)

Statistical Science, Vol. 16, No. 3. (August 2001), pp. 199-231,


There are two cultures in the use of statistical modeling to reach conclusions from data. One assumes that the data are generated by a given stochastic data model. The other uses algorithmic models and treats the data mechanism as unknown. The statistical community has been committed to the almost exclusive use of data models. This commitment has led to irrelevant theory, questionable conclusions, and has kept statisticians from working on a large range of interesting current problems. Algorithmic modeling, both in ...


Nigeria demographic and health survey 2013



[Excerpt:: Foreword] Nigeria Demographic and Health Survey (NDHS) 2013 is the fourth survey of its kind to be implemented by the National Population Commission (NPC). As the agency charged with the responsibility of collecting, collating, and analysing demographic data, the Commission has been unrelenting in its efforts to provide reliable, accurate, and up-to-date data for the country. We hope that information contained in this report will assist policymakers and programme managers in monitoring and designing programmes and strategies for improving health and family planning services in Nigeria. ...


Nigeria demographic and health survey 2008



[Excerpt: Summary of findings] The 2008 Nigeria Demographic Health Survey (NDHS) is a nationally representative survey of 33,385 women age 15-49 and 15,486 men age 15-59. The 2008 NDHS is the fourth comprehensive survey conducted in Nigeria as part of the Demographic and Health Surveys (DHS) programme. The data are intended to furnish programme managers and policymakers with detailed information on levels and trends in fertility; nuptiality; sexual activity; fertility preferences; awareness and use of family planning methods; infants and young children feeding practices; nutritional status of mothers and young children; early childhood mortality and ...


WHO child growth standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age - Methods and development



[:Executive summary: Methods and development] In 1993 the World Health Organization (WHO) undertook a comprehensive review of the uses and interpretation of anthropometric references. The review concluded that the NCHS/WHO growth reference, which had been recommended for international use since the late 1970s, did not adequately represent early childhood growth and that new growth curves were necessary. The World Health Assembly endorsed this recommendation in 1994. In response WHO undertook the Multicentre Growth Reference Study (MGRS) between 1997 and 2003 to generate ...


Stacked generalization

Neural Networks, Vol. 5, No. 2. (January 1992), pp. 241-259,


This paper introduces stacked generalization, a scheme for minimizing the generalization error rate of one or more generalizers. Stacked generalization works by deducing the biases of the generalizer(s) with respect to a provided learning set. This deduction proceeds by generalizing in a second space whose inputs are (for example) the guesses of the original generalizers when taught with part of the learning set and trying to guess the rest of it, and whose output is (for example) the correct guess. When ...


Hierarchical Bayesian modeling

In Subjective and Objective Bayesian Statistics: Principles, Models, and Applications, Second Edition (25 November 2002), pp. 336-358,
edited by S. James Press


[Excerpt: Introduction] Hierarchical modeling is a widely used approach to building complex models by specifying a series of more simple conditional distributions. It naturally lends itself to Bayesian inference, especially using modern tools for Bayesian computation. In this chapter we first present essential concepts of hierarchical modeling, and then suggest its generality by presenting a series of widely used specific models. [...] [\n] [...] [Summary] In this chapter we have introduced hierarchical modeling as a very general approach to specifying complex models through a ...


Paintings predict the distribution of species, or the challenge of selecting environmental predictors and evaluation statistics

Global Ecology and Biogeography, Vol. 27, No. 2. (February 2018), pp. 245-256,


[Aim] Species distribution modelling, a family of statistical methods that predicts species distributions from a set of occurrences and environmental predictors, is now routinely applied in many macroecological studies. However, the reliability of evaluation metrics usually employed to validate these models remains questioned. Moreover, the emergence of online databases of environmental variables with global coverage, especially climatic, has favoured the use of the same set of standard predictors. Unfortunately, the selection of variables is too rarely based on a careful examination of ...


Applied regression and multilevel/hierarchical models



Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces and demonstrates a wide variety of models, at the same time instructing the reader in how to fit these models using freely available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen in the authors’ own applied research, with programming code provided for each one. Topics ...


On the projection of future fire danger conditions with various instantaneous/mean-daily data sources

Climatic Change, Vol. 118, No. 3-4. (2013), pp. 827-840,


Fire danger indices are descriptors of fire potential in a large area, and combine a few variables that affect the initiation, spread and control of forest fires. The Canadian Fire Weather Index (FWI) is one of the most widely used fire danger indices in the world, and it is built upon instantaneous values of temperature, relative humidity and wind velocity at noon, together with 24 hourly accumulated precipitation. However, the scarcity of appropriate data has motivated the use of daily mean ...


Redefine statistical significance

Nature Human Behaviour, Vol. 2, No. 1. (1 September 2017), pp. 6-10,


We propose to change the default P-value threshold for statistical significance for claims of new discoveries from 0.05 to 0.005 ...


Seeking for the rational basis of the Median Model: the optimal combination of multi-model ensemble results

Atmospheric Chemistry and Physics, Vol. 7, No. 24. (11 December 2007), pp. 6085-6098,


In this paper we present an approach for the statistical analysis of multi-model ensemble results. The models considered here are operational long-range transport and dispersion models, also used for the real-time simulation of pollutant dispersion or the accidental release of radioactive nuclides. [\n] We first introduce the theoretical basis (with its roots sinking into the Bayes theorem) and then apply this approach to the analysis of model results obtained during the ETEX-1 exercise. We recover some interesting results, supporting the heuristic approach ...


An assessment of forest biomass maps in Europe using harmonized national statistics and inventory plots

Forest Ecology and Management, Vol. 409 (February 2018), pp. 489-498,


[Highlights] [::] We assessed four biomass maps for Europe using harmonized biomass reference data. [::] The harmonized statistics were derived from ∼430,000 plots from 26 countries. [::] All maps overestimated at low biomass and underestimated at high biomass. [::] All maps had an overall negative bias (23–43 Mg ha−1 at national level). [::] The maps relative errors was 29–40% at national level and 63–72% at cell level. [Abstract] Maps of aboveground forest biomass based on different input data and modelling approaches have been recently produced for Europe, opening up the ...


Regulation and stability of host-parasite population interactions: I - Regulatory processes

Journal of Animal Ecology, Vol. 47, No. 1. (February 1978), pp. 219-247,


[::1] Several models describing the dynamics of host-parasite associations are discussed. [::2] The models contain the central assumption that the parasite increases the rate of host mortalities. The parasite induced changes in this rate are formulated as functions of the parasite numbers per host and hence of the statistical distribution of the parasites within the host population. [::3] The parameters influencing the ability of the parasite to regulate the growth of its host's population, and the stability of parasite induced equilibria, ...


K-groups: a generalization of K-means clustering

(12 Nov 2017)


We propose a new class of distribution-based clustering algorithms, called k-groups, based on energy distance between samples. The energy distance clustering criterion assigns observations to clusters according to a multi-sample energy statistic that measures the distance between distributions. The energy distance determines a consistent test for equality of distributions, and it is based on a population distance that characterizes equality of distributions. The k-groups procedure therefore generalizes the k-means method, which separates clusters that have different means. We propose two k-groups algorithms: k-groups by first variation; and k-groups by ...


Malaria prevalence metrics in low- and middle-income countries: an assessment of precision in nationally-representative surveys

Malaria Journal, Vol. 16 (21 November 2017), 475,


[Background] One pillar to monitoring progress towards the Sustainable Development Goals is the investment in high quality data to strengthen the scientific basis for decision-making. At present, nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring, and evaluation of health metrics. However, little is known about the optimal precisions of various population-level health and development indicators that remains unquantified in nationally-representative household surveys. Here, a retrospective analysis of the precision of prevalence from these surveys was ...


Impact of population growth and population ethics on climate change mitigation policy

Proceedings of the National Academy of Sciences, Vol. 114, No. 46. (14 November 2017), pp. 12338-12343,


[Significance] We investigate how future population growth is relevant to climate change policy. The answer depends importantly on ethical questions about whether our ultimate goal should be to increase the number of people who are happy or rather to increase the average level of people’s happiness. We calculate the best (optimal) emissions reduction pathway given each of these two different goals that society might have and calculate how much cheaper it would be to avoid dangerous interference with the climate given a ...


How population growth relates to climate change

Proceedings of the National Academy of Sciences, Vol. 114, No. 46. (14 November 2017), pp. 12103-12105,


[Excerpt] Currently, around 7.5 billion people live on our planet and scenarios for the future show a plausible range from 8.5 to over 12 billion before the population will level off or start to decline, depending on the future course of fertility and mortality (1, 2). These people will also have to cope with the consequences of climate change that may be in the range of 1.5 °C to more than 3 °C, depending on the scale of mitigation efforts. The ...


Bridging national and reference definitions for harmonizing forest statistics

Forest Science (June 2012), pp. 214-223,


Harmonization is the process of making information and estimates comparable across administrative borders. The degree to which harmonization succeeds depends on many factors, including the conciseness of the definitions, the availability and quality of data, and the methods used to convert an estimate according to a local definition to an estimate according to the reference definition. Harmonization requires the availability and use of common reference definitions and methods for converting from estimates based on national definitions to estimates based on reference ...


Big names in statistics want to shake up much-maligned P value

Nature, Vol. 548, No. 7665. (26 July 2017), pp. 16-17,


One of scientists’ favourite statistics — the P value — should face tougher standards, say leading researchers. [Excerpt] Science is in the throes of a reproducibility crisis, and researchers, funders and publishers are increasingly worried that the scholarly literature is littered with unreliable results. Now, a group of 72 prominent researchers is targeting what they say is one cause of the problem: weak statistical standards of evidence for claiming new discoveries. [\n] In many disciplines the significance of findings is judged by ...


Fire situation in Greece

International Forest Fire News, Vol. 23 (2000), pp. 76-83


[Excerpt: Conclusions and Outlook] As can be seen, Greece has a serious fire problem. The money and effort devoted to coping with the problem is significant. Actually, especially in terms of aerial forces, the country should probably be rated first in the world on a per-hectare-protected basis. However, the poor results of the last few years clearly indicate that there is need for improvement, especially in regard to knowledge and organization of the whole effort. Also, there is a clear need for ...


Resampling methods for meta-model validation with recommendations for evolutionary computation

Evolutionary Computation, Vol. 20, No. 2. (16 February 2012), pp. 249-275,


Meta-modeling has become a crucial tool in solving expensive optimization problems. Much of the work in the past has focused on finding a good regression method to model the fitness function. Examples include classical linear regression, splines, neural networks, Kriging and support vector regression. This paper specifically draws attention to the fact that assessing model accuracy is a crucial aspect in the meta-modeling framework. Resampling strategies such as cross-validation, subsampling, bootstrapping, and nested resampling are prominent methods for model validation and ...


Combining multiple classifiers: an application using spatial and remotely sensed information for land cover type mapping

Remote Sensing of Environment, Vol. 74, No. 3. (December 2000), pp. 545-556,


This article discusses two new methods for increasing the accuracy of classifiers used land cover mapping. The first method, called the product rule, is a simple and general method of combining two or more classification rules as a single rule. Stacked regression methods of combining classification rules are discussed and compared to the product rule. The second method of increasing classifier accuracy is a simple nonparametric classifier that uses spatial information for classification. Two data sets used for land cover mapping ...


Bagging ensemble selection for regression

In AI 2012: Advances in Artificial Intelligence, Vol. 7691 (2012), pp. 695-706,


Bagging ensemble selection (BES) is a relatively new ensemble learning strategy. The strategy can be seen as an ensemble of the ensemble selection from libraries of models (ES) strategy. Previous experimental results on binary classification problems have shown that using random trees as base classifiers, BES-OOB (the most successful variant of BES) is competitive with (and in many cases, superior to) other ensemble learning strategies, for instance, the original ES algorithm, stacking with linear regression, random forests or boosting. Motivated by ...


Bagging ensemble selection

In AI 2011: Advances in Artificial Intelligence, Vol. 7106 (2011), pp. 251-260,


Ensemble selection has recently appeared as a popular ensemble learning method, not only because its implementation is fairly straightforward, but also due to its excellent predictive performance on practical problems. The method has been highlighted in winning solutions of many data mining competitions, such as the Netflix competition, the KDD Cup 2009 and 2010, the UCSD FICO contest 2010, and a number of data mining competitions on the Kaggle platform. In this paper we present a novel variant: bagging ensemble selection. ...


Cause dolose e colpose degli incendi in Sicilia: proposte per la rimozione degli interessi e dei bisogni alla base del fenomeno

In Atti del convegno: incendi boschivi e rurali in Sardegna - Dall’analisi delle cause alle proposte d’intervento (2005), pp. 177-185


[:Excerpt: Index of sections (translated from Italian)] [::] Sicily - geographical overview and orographic structure [::] forest areas [::] protected areas [::] forest fires [::] the causes of fires [::] proposals for removing stakes and needs behind the phenomenon [\n] [\n] [:(Original language) Indice delle sezioni] [::] Sicilia - inquadramento geografico e caratteristiche orografiche [::] superfici boscate [::] aree protette [::] incendi boschivi [::] le cause degli incendi [::] proposte per la rimozione degli interessi e bisogni alla base del fenomeno ...


Spatiotemporal variations in wildfire regime and exposure for Sardinia, Italy

In Atti del Secondo Congresso Internazionale di Selvicoltura = Proceedings of the Second International Congress of Silviculture (2015), pp. 975-981,


[Summary] Over the past decades several studies highlighted the increasing risk in the occurrence of large and severe wildfires as well as significant variation in fire regime pattern. In the Mediterranean basin, Sardinia (Italy) has seen a marked reduction in the annual area burned since the 1980s, with a sharp variation in mid-‘90s. Despite this downward trend wildfires still cause considerable financial losses, damages to natural ecosystems, accidents and fatalities. Therefore, efficient wildfire exposure and risk estimation as well as ...



In NIST/SEMATECH e-Handbook of Statistical Methods (2012),


[Excerpt: Definitions of order statistics and ranks] For a series of measurements Y1, …, YN, denote the data ordered in increasing order of magnitude by Y〈1〉, …, Y〈N〉. These ordered data are called order statistics. If Y〈j〉 is the order statistic that corresponds to the measurement Yᵢ, then the rank for Yᵢ is j; i.e., [::] Y〈j〉 ∼ Yᵢ, rᵢ=j. [Definition of percentiles] Order statistics provide a way of estimating proportions of the data that should fall above and below a ...


Sample quantiles in statistical packages

The American Statistician, Vol. 50, No. 4. (1 November 1996), pp. 361-365,


There are a large number of different definitions used for sample quantiles in statistical computer packages. Often within the same package one definition will be used to compute a quantile explicitly, while other definitions may be used when producing a boxplot, a probability plot, or a QQ plot. We compare the most commonly implemented sample quantile definitions by writing them in a common notation and investigating their motivation and some of their properties. We argue that there is a need to ...


Remote sensing monitoring of land restoration interventions in semi-arid environments with a before–after control-impact statistical design

International Journal of Applied Earth Observation and Geoinformation, Vol. 59 (July 2017), pp. 42-52,


[Highlights] [::] A rapid, standardised and objective assessment of the biophysical impact of restoration interventions is proposed. [::] The intervention impact is evaluated by a before–after control-impact sampling design. [::] The method provides a statistical test of the no-change hypothesis and the estimation of the relative magnitude of the change. [::] The method is applicable to NDVI and other remote sensing-derived variables. [Abstract] Restoration interventions to combat land degradation are carried out in arid and semi-arid areas to improve vegetation cover and land productivity. Evaluating the success ...


Countering European brain drain

Science, Vol. 356, No. 6339. (19 May 2017), pp. 695-696,


[Excerpt] [...] Mobile European researchers who went to the United States were significantly more likely to report strong positive career effects than their mobile peers who moved within the European Union (EU) (up to twice as high) [...] In search of a possible “elite” brain drain from Europe, we examined return rates for a sample of Europeans pursuing Ph.D. degrees in economics in the United States (3). Those better students who received Ph.D. degrees from top U.S. institutes are more likely ...


Willingness to share research data is related to the strength of the evidence and the quality of reporting of statistical results

PLOS ONE, Vol. 6, No. 11. (2 November 2011), e26828,


The widespread reluctance to share published research data is often hypothesized to be due to the authors' fear that reanalysis may expose errors in their work or may produce conclusions that contradict their own. However, these hypotheses have not previously been studied systematically. We related the reluctance to share research data for reanalysis to 1148 statistically significant results reported in 49 papers published in two major psychology journals. We found the reluctance to share data to be associated with weaker evidence ...


Fuzziness vs. probability

International Journal of General Systems, Vol. 17, No. 2-3. (June 1990), pp. 211-240,


Fuzziness is explored as an alternative to randomness for describing uncertainty. The new sets-as-points geometric view of fuzzy sets is developed. This view identifies a fuzzy set with a point in a unit hypercube and a nonfuzzy set with a vertex of the cube. Paradoxes of two-valued logic and set theory, such as Russell's paradox, correspond to the midpoint of the fuzzy cube. The fundamental questions of fuzzy theory—How fuzzy is a fuzzy set? How much is one fuzzy set a ...


Impact factors: no totum pro parte by skewness of citation

Cardiovascular Research, Vol. 61, No. 2. (01 February 2004), pp. 201-203,


Citation of the various papers published in one and the same journal is highly skewed. Journals with a high impact factor obtain this high value by frequent citation of only a limited number of their papers and, on the other hand, journals with low impact factors publish many papers that remain uncited [1]. Thus, mere publication of a paper in a given journal cannot be regarded as a quality marker of that particular paper [2], it just means that the authors ...


Detecting long-range correlations with detrended fluctuation analysis

Physica A: Statistical Mechanics and its Applications, Vol. 295, No. 3-4. (June 2001), pp. 441-454,


We examine the detrended fluctuation analysis (DFA), which is a well-established method for the detection of long-range correlations in time series. We show that deviations from scaling which appear at small time scales become stronger in higher orders of DFA, and suggest a modified DFA method to remove them. The improvement is necessary especially for short records that are affected by non-stationarities. Furthermore, we describe how crossovers in the correlation behavior can be detected reliably and determined quantitatively and show how ...


Statistical significance of seasonal warming/cooling trends

Proceedings of the National Academy of Sciences, Vol. 114, No. 15. (11 April 2017), pp. E2998-E3003,


[Significance] The question whether a seasonal climatic trend (e.g., the increase of spring temperatures in Antarctica in the last decades) is of anthropogenic or natural origin is of great importance because seasonal climatic trends may considerably affect ecological systems, agricultural yields, and human societies. Previous studies assumed that the seasonal records can be treated as independent and are characterized by short-term memory only. Here we show that both assumptions, which may lead to a considerable overestimation of the trend significance, do not ...


Mapping indicators of female welfare at high spatial resolution



Improved understanding of geographic variation and inequity in health status, wealth, and access to resources within countries is increasingly being recognized as central to meeting development goals. Development and health indicators assessed at national scales conceal important inequities, with the rural poor often least well represented. High-resolution data on key social and health indicators are fundamental for targeting limited resources, especially where development funding has recently come under increased pressure. Globally, around 80% of countries regularly produce sex-disaggregated statistics at a ...


  1. Alegana, V.A., Atkinson, P.M., Pezzulo, C., Sorichetta, A., Weiss, D., Bird, T., ErbachSchoenberg, E., Tatem, A.J., 2015. Fine resolution mapping of population age-structures for health and development applications. Journal of The Royal Society Interface 12 (105), 20150073+. .
  2. Banerjee, S., Gelfand, A.E., Polasek, W., 2000. Geostatistical modelling for spatial interaction data with application to postal service performance. Journal of statistical planning and inference 90(1), 87-105. .

Exploring the high-resolution mapping of gender-disaggregated development indicators

Journal of The Royal Society Interface, Vol. 14, No. 129. (05 April 2017), 20160825,


Improved understanding of geographical variation and inequity in health status, wealth and access to resources within countries is increasingly being recognized as central to meeting development goals. Development and health indicators assessed at national or subnational scale can often conceal important inequities, with the rural poor often least well represented. The ability to target limited resources is fundamental, especially in an international context where funding for health and development comes under pressure. This has recently prompted the exploration of the potential ...


Supplementary Information from Exploring the high-resolution mapping of gender disaggregated development indicators



[Excerpt: Datasets] The Demographic and Health Surveys (DHS) is a program of national household surveys implemented across a large number of LMICs. The DHS Program collects and analyses data on population demographic and health characteristics through more than 300 surveys in over 90 countries. The gender-disaggregated data we investigated in this report come from DHS datasets. [\n] [...] [Models specification] [::Bayesian model specification] The Gaussian Function (GF) in INLA is represented as a Gaussian Markov Random Function (GMRF). Computations in INLA are carried out using the GMRF by approximating a ...


  1. Alegana, V.A., Atkinson, P.M., Pezzulo, C., Sorichetta, A., Weiss, D., Bird, T., ErbachSchoenberg, E., Tatem, A.J., 2015. Fine resolution mapping of population age-structures for health and development applications. Journal of The Royal Society Interface 12 (105), 20150073+. .
  2. Bosco, C., de Rigo, D., Dijkstra, T.A., Sander, G., Wasowski, J., 2013. Multi-scale robust modelling of landslide susceptibility: regional rapid assessment and catchment robust fuzzy ensemble. IFIP Advances in Information and Communication Technology

Data-driven predictions in the science of science

Science, Vol. 355, No. 6324. (03 February 2017), pp. 477-480,


The desire to predict discoveries—to have some idea, in advance, of what will be discovered, by whom, when, and where—pervades nearly all aspects of modern science, from individual scientists to publishers, from funding agencies to hiring committees. In this Essay, we survey the emerging and interdisciplinary field of the “science of science” and what it teaches us about the predictability of scientific discovery. We then discuss future opportunities for improving predictions derived from the science of science and its potential impact, ...


Improving generalized regression analysis for the spatial prediction of forest communities

Journal of Biogeography, Vol. 33, No. 10. (October 2006), pp. 1729-1749,


Abstract Aim  This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location  State of Vaud, ...


Estimating abundance from repeated presence-absence data or point counts

Ecology, Vol. 84, No. 3. (March 2003), pp. 777-790,[0777:eafrpa];2


We describe an approach for estimating occupancy rate or the proportion of area occupied when heterogeneity in detection probability exists as a result of variation in abundance of the organism under study. The key feature of such problems, which we exploit, is that variation in abundance induces variation in detection probability. Thus, heterogeneity in abundance can be modeled as heterogeneity in detection probability. Moreover, this linkage between heterogeneity in abundance and heterogeneity in detection probability allows one to exploit a heterogeneous ...


Multivariate binary discrimination by the kernel method

Biometrika, Vol. 63, No. 3. (1 December 1976), pp. 413-420,


An extension of the kernel method of density estimation from continuous to multivariate binary spaces is described. Its simple nonparametric nature together with its consistency properties make it an attractive tool in discrimination problems, with some advantages over already proposed parametric counterparts. The method is illustrated by an application to a particular medical diagnostic problem. Simple extensions of the method to categorical data and to data of mixed binary and continuous form are indicated. ...


Framework for making better predictions by directly estimating variables’ predictivity

Proceedings of the National Academy of Sciences, Vol. 113, No. 50. (13 December 2016), pp. 14277-14282,


[Significance] Good prediction, especially in the context of big data, is important. Common approaches to prediction include using a significance-based criterion for evaluating variables to use in models and evaluating variables and models simultaneously for prediction using cross-validation or independent test data. The first approach can lead to choosing less-predictive variables, because significance does not imply predictivity. The second approach can be improved through considering a variable’s predictivity as a parameter to be estimated. The literature currently lacks measures that do ...


Statistical analysis

In Science: editorial policies (2016)


[Excerpt: Statistical analysis] Generally, authors should describe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to verify the results. [::] Data pre-processing steps such as transformations, re-coding, re-scaling, normalization, truncation, and handling of below detectable level readings and outliers should be fully described; any removal or modification of data values must be fully acknowledged and justified. [::] [...] [::] The number of sampled units, N, upon which each reported statistic is based must be stated. [::] For continuous ...


Poisson point process models solve the “pseudo-absence problem” for presence-only data in ecology

The Annals of Applied Statistics, Vol. 4, No. 3. (September 2010), pp. 1383-1402,


Presence-only data, point locations where a species has been recorded as being present, are often used in modeling the distribution of a species as a function of a set of explanatory variables—whether to map species occurrence, to understand its association with the environment, or to predict its response to environmental change. Currently, ecologists most commonly analyze presence-only data by adding randomly chosen “pseudo-absences” to the data such that it can be analyzed using logistic regression, an approach which has weaknesses in ...


Passing the point of no return

Science, Vol. 354, No. 6316. (02 December 2016), pp. 1109-1109,


[Excerpt] In the field of ecology, regime shifts are massive changes in function and character that occur when an ecosystem passes a tipping point. Regime shifts sometimes have severe consequences for human well-being through losses of ecosystem services, including desertification in arid regions and marine fisheries collapses. These changes are difficult to predict and sometimes impossible to reverse. For these reasons, understanding how to anticipate and prevent regime shifts is one of the most important challenges faced by environmental scientists. [\n] Theoretical analyses ...


Characteristics and controls of extremely large wildfires in the western Mediterranean Basin

Journal of Geophysical Research: Biogeosciences, Vol. 121, No. 8. (August 2016), pp. 2141-2157,


Large fires account for a disproportionally high percentage of area burned with potentially severe environmental and socioeconomic impacts. This study characterizes extremely large fires (ELFs; 2500–24,843 ha) in Portugal (1998–2013) and the concomitant fuel and weather conditions, analyzing the response of ELF size to their variation. ELF burned less shrubland-grassland (33% of the total ELF area) than forest (59% of total), the latter primarily composed by pine and pine-eucalypt. High fuel hazard was the norm, as indicated by median values of 0.98 ...


Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: evaluation on the present climate

Journal of Geophysical Research, Vol. 116, No. D16. (18 August 2011),


A statistical bias correction technique is applied to a set of high-resolution climate change simulations for Europe from 11 state-of-the-art regional climate models (RCMs) from the project ENSEMBLES. Modeled and observed daily values of mean, minimum and maximum temperature and total precipitation are used to construct transfer functions for the period 1961–1990, which are then applied to the decade 1991–2000, where the results are evaluated. By using a large ensembles of model runs and a long construction period, we take into ...


Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: analysis of the climate change signal

Journal of Geophysical Research: Atmospheres, Vol. 117, No. D17. (16 September 2012), D17110,


A statistical bias correction technique is applied to twelve high-resolution climate change simulations of temperature and precipitation over Europe, under the SRES A1B scenario, produced for the EU project ENSEMBLES. The bias correction technique is based on a transfer function, estimated on current climate, which affects the whole Probability Distribution Function (PDF) of variables, and which is assumed constant between the current and future climate. The impact of bias correction on 21st Century projections, their inter-model variability, and the climate change ...

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