deltamethod.special | R Documentation |
This function computes the delta method std errors or v-c matrix for a sum, cumsum (vector of cummulative sums), prod (product), or cumprod(vector of cummulative products) of a set of estimates.
deltamethod.special(function.name, mean, cov, ses = TRUE)
function.name |
Quoted character string of either "sum", "cumsum", "prod" or "cumprod" |
mean |
vector of estimates used in the function |
cov |
variance-covariance matrix of the estimates |
ses |
if TRUE it returns a vector of estimated standard errors of the function of the estimates and if FALSE it returns the variance-covariance matrix |
This function computes the delta method std errors or v-c matrix for a sum, cumsum (vector of cummulative sums), prod (product), or cumprod(vector of cummulative products). It uses the function deltamethod from the msm package and constructs the necessary formula for these special cases. It will load the msm pacakge but assumes that it has already been installed. See the msm documentation for a complete description on how the deltamethod function works. If ses=TRUE, it returns a vector of std errors for each of functions of the estimates contained in mean. If ses=F, then it returns a v-c matrix for the functions of the estimates contained in mean. cov is the input v-c matrix of the estimates.
either a vector of standard errors (ses=TRUE) or a variance-covariance matrix (ses=FALSE)
Jeff Laake
# This example is excluded from testing to reduce package check time # # The following are examples only to demonstrate selecting different # model sets for adjusting chat and showing model selection table. # It is not a realistic analysis. # data(dipper) mod=mark(dipper,model.parameters=list(Phi=list(formula=~time)),delete=TRUE) rr=get.real(mod,"Phi",se=TRUE,vcv=TRUE) deltamethod.special("prod",rr$estimates$estimate[1:6],rr$vcv.real) deltamethod.special("cumprod",rr$estimates$estimate[1:6],rr$vcv.real,ses=FALSE) deltamethod.special("sum",rr$estimates$estimate[1:6],rr$vcv.real) deltamethod.special("cumsum",rr$estimates$estimate[1:6],rr$vcv.real,ses=FALSE)
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