Pedro J Leitão
Biographic Data
| ID | 7877124 |
|---|---|
| NAME | Pedro J Leitão |
| GIVEN NAMES | Pedro J |
| FAMILY NAME | Leitão |
| SIGNATURE | LEITÃO P J |
| AFFILIATIONS | Humboldt-Universität zu Berlin |
| ORCID | 0000-0003-3038-9531 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2013 |
| H-INDEX | 0 |
Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees
Collinearity
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
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…
No prominent works on this page.
Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees
Collinearity
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
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 works) · Mathematics (2 works) · Regression analysis (2 works) · Statistics (2 works) · Abandonment (legal) (1 work) · Agriculture (1 work) · Archaeology (1 work) · Bivariate analysis (1 work) · Categorical variable (1 work) · Climate Change and Health Impacts (1 work)