A contingency table presents the joint density of one or more categorical variables. Each entry in a contingency table is a count of the number of times a particular set of factors levels occurs in the dataset. For example, consider a list of plant ...
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Converting R contingency tables to data frames
A contingency table presents the joint density of one or more categorical variables. Each entry in a contingency table is a count of the number of times a particular set of factors levels occurs in the dataset. For example, consider a list of plant ...
Extracting Raster Values from Points in R and GRASS
A common task in GIS analysis is to extract the value of a remotely sensed environmental variable at a point location. For instance we may wish to extract the elevation of a field plot from a digital elevation model. The elevation data is a raster (i.e. grid) and the plots are a point shapefile (or a simple text file of X,...
Extracting Raster Values from Points in R and GRASS
A common task in GIS analysis is to extract the value of a remotely sensed environmental variable at a point location. For instance we may wish to extract the elevation of a field plot from a digital elevation model. The elevation data is a raster (i.e. grid) and the plots are a point shapefile (or a simple text file of X,...
Power Analysis for mixed-effect models in R
The power of a statistical test is the probability that a null hypothesis will be rejected when the alternative hypothesis is true. In lay terms, power is your ability to refine or "prove" your expectations from the data you collect. The most frequent...
Power Analysis for mixed-effect models in R
The power of a statistical test is the probability that a null hypothesis will be rejected when the alternative hypothesis is true. In lay terms, power is your ability to refine or "prove" your expectations from the data you collect. The most frequent...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
