Imprecise Inferential Framework for Poisson Sampling Model


[Up] [Top]

Documentation for package ‘imPois’ version 0.0.7.5

Help Pages

imPois-package Imprecise Inferential Framework for Poisson Sampling Model
cgf Comupting Normalizing Constant of Bickis and Lee's Probability Distribution
cgf.ztrunc Comupting Normalizing Constant of Bickis and Lee's Probability Distribution
dcpm Imprecise Probability Distribution
dcpm.ztrunc Imprecise Probability Distribution
evfn Expected Value of Canonical Variable
evfn.ztrunc Expected Value of Canonical Variable
fn.evfn Objective And Gradient Vector Needed For Optimization
gr.evfn Objective And Gradient Vector Needed For Optimization
imPois Imprecise Inferential Framework for Poisson Sampling Model
iprior Characterize Imprecise Prior
kcpm Kernel of Imprecise Probability Measure Formulated By Bickis and Lee
kcpm.ztrunc Kernel of Imprecise Probability Measure Formulated By Bickis and Lee
kcpm.ztrunc_t Kernel of Imprecise Probability Measure Formulated By Bickis and Lee
kcpm_m Kernel of Imprecise Probability Measure Formulated By Bickis and Lee
lapprox.ztrunc Expected Value of Canonical Variable
mh.ztrunc Expected Value of Canonical Variable
pbox Plotting Imprecise Objects
pcpm Imprecise Probability Distribution
pcpm.ztrunc Imprecise Probability Distribution
plot.impinf Plotting Imprecise Objects
print.summary.impinf Print Imprecise Objects
summary.impinf Summary of 'impinf' object
update.impinf Applying Bayes Rule