MetGen (version 0.5)

fit.glm: Fitting Generalized Linear Models

Description

fit.glm is used to fit generalized linear models, taking account of covariates specified in the argument list

Usage

fit.glm(var.name, dep.var=NULL, geocov=TRUE, large.var, seasonal = TRUE, 
speriod = 365.25, diurnal = TRUE, dperiod = 24, spatave=TRUE, lagspat,
movave = TRUE, bwM = 48, lagmov, spatmovave= TRUE, bwSM = 48, lagspatmov, 
lagvar, add.cov= FALSE, others=NULL,  fam.glm = "gaussian", data)

Arguments

var.name

character that forms the name of the climatic variable to be fitted

dep.var

character that forms the name of depending variables

geocov

logical value indicating whether geographical information is part of covariates set

large.var

character object that forms the name of the large scale variable

seasonal

logical value indicating whether seasonal effects are among the covariates defined for the variable that will be fitted

speriod

A numeric vector that contains the lenght of seasonal cycles defined for the variable of interest

diurnal

logical value indicating whether diurnal effects are among the covariates defined for the variable that will be fitted

dperiod

A numeric vector that contain the lenght of diurnal cycles defined for the variable of interest

spatave

logical value indicating whether spatial average effects are among the covariates defined for the variable that will be fitted

lagspat

Numeric vector indicating values of lags performed for the spatial average

movave

logical value indicating whether moving average effects are among the covariates defined for the variable that will be fitted

bwM

A numeric vector that contains the bandwidth defined for the moving average

lagmov

Numeric vector indicating values of lags performed for the moving average

spatmovave

logical value indicating whether spatial moving average effects are among the covariates defined for the variable that will be fitted

bwSM

A numeric vector that contains the bandwidth defined for the spatial moving average

lagspatmov

Numeric vector indicating values of lags performed for the spatial moving average

lagvar

Numeric vector indicating values of lags performed for the variable

add.cov

logical value indicatng whether we have an additional covariates defined for the variable to fit

others

character that forms the name of additional covariates specified for the variable to fit

fam.glm

family objects to specify probability distribution that will be used for the simulation mode ("gaussian", "gaussian-hetero", "binomial" or "Gamma")

data

data frame that contains a variable named "dates" in chron format, possibly including times, geographical information for the measurement site, climatic variable to be fitted and all different covariates that will be used to fit the variable of interest

Value

value returned is a variable fitted which inherits from the class "lm"

See Also

diurnal.effect, seasonal.effect, lagged.effect

Examples

# NOT RUN {
##Create a new data that contains climatic series and all effects that will be 
##used as covariates for the variable to fit
mat_effects <- seasonal.effect(myclimatic_data, period=c(365,183))
mat_effects <- diurnal.effect(mat_effects, period=24)
mat_effects <- lagged.effect(mat_effects, "temp",2, nstat=3)
##Add a large scale variable
mat_effects$t2m <- rnorm(nrow(myclimatic_data), mean=25, sd=1)
temp_fitted <- fit.glm("temp", dep.var = "Rh", geocov=TRUE, large.var="t2m", 
seasonal = TRUE, speriod = c(365, 183), diurnal = TRUE, dperiod = 24, 
spatave = FALSE, movave = FALSE, spatmovave= FALSE, add.cov = FALSE, others = NULL, 
lagvar=2, fam.glm = "gaussian", data=mat_effects)
# }