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Pedro J Leitão

Datos Biográficos

ID7877124
NOMBREPedro J Leitão
NOMBRESPedro J
APELLIDOLeitão
FIRMALEITÃO P J
AFILIACIONESHumboldt-Universität zu Berlin
ORCID0000-0003-3038-9531
VERIFICADOSí
TOTAL DE OBRAS3
TOTAL DE CITAS0
OBRAS COMO AUTOR3
OBRAS COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2013
AÑO MÁS RECIENTE DE PUBLICACIÓN2013
ÍNDICE H0
  • Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees

    Open Access•Daniel Müller, Pedro J Leitão et al.•ARTICLE•Agricultural Systems•2013

  • Collinearity

    Open Access•Carsten F Dormann, Jane Elith et al.•ARTICLE•Ecography•2013

    Collinearity refers to the non independence of predictor variables, usually in a regression‐type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one …

  • Assessing Weather Effects on Dengue Disease in Malaysia

    Open Access•Yoon Ling Cheong, Katrin Burkart et al.•ARTICLE•International Journal of…•2013

    The number of dengue cases has been increasing on a global level in recent years, and particularly so in Malaysia, yet little is known about the effects of weather for identifying the short-term risk of dengue for the population. The aim of this paper is to estimate the weather effects on dengue disease accounting for non-linear temporal effects in Selangor, Kuala Lumpur and Putrajaya, Malaysia, from 2008 to 2010. We selected the weather paramete…

Sin obras prominentes en esta página.

  • Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees

    Open Access•Daniel Müller, Pedro J Leitão et al.•ARTICLE•Agricultural Systems•2013

  • Collinearity

    Open Access•Carsten F Dormann, Jane Elith et al.•ARTICLE•Ecography•2013

    Collinearity refers to the non independence of predictor variables, usually in a regression‐type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one …

  • Assessing Weather Effects on Dengue Disease in Malaysia

    Open Access•Yoon Ling Cheong, Katrin Burkart et al.•ARTICLE•International Journal of…•2013

    The number of dengue cases has been increasing on a global level in recent years, and particularly so in Malaysia, yet little is known about the effects of weather for identifying the short-term risk of dengue for the population. The aim of this paper is to estimate the weather effects on dengue disease accounting for non-linear temporal effects in Selangor, Kuala Lumpur and Putrajaya, Malaysia, from 2008 to 2010. We selected the weather paramete…

Geography (2 obras) · Mathematics (2 obras) · Regression analysis (2 obras) · Statistics (2 obras) · Abandonment (legal) (1 obra) · Agriculture (1 obra) · Archaeology (1 obra) · Bivariate analysis (1 obra) · Categorical variable (1 obra) · Climate Change and Health Impacts (1 obra)

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