desc {GenEst}

Descriptive statistics for a fitted CP model

Description

Given a cpm object, calculate convenient descriptive statistics, including the median CP, specified rI statistics, and pda and pdb statistics for the fitted model (EoA parameterization), and location and scale parameters for the fitted model (survival package parameterization) along with estimated CIs.

Usage

desc(model_CP, Ir = c(1, 3, 7, 14, 28), CL = 0.9, nsim = 10000)

Arguments

model_CP

A fitted CP model (cpm object)

Ir

The intervals for which to calculate the r statistics

CL

The confidence level for the CIs.

nsim

Number of simulation draws for estimating CIs

Details

The CIs for the r statistics (and the medianCP for the Weibull) ara based on simulation of the pda and pdb parameters, calculation of the statistics, and taking the empirical distribution of the simulated values. Other CIs are based on the assumed bivariate normal distributions of the appropriately transformed l and s parameters in the fitted model using beta_hat and varbeta.

NOTE: rI is the probability that a carcass that arrives at a uniform random time in an interval of I days will persist until the first search after arrival.

Value

Matrix of point and interval estimates for the median CP and the r statistics for the specified intervals. The matrix is assigned to class descCP that is simply a matrix with dimensions ncell x (1 + 3*(5 + length(Ir))), column names that give the number of observations in each cell, statistic name and upper and lower bounds (in triplets), and row names giving the names of the cells. CL, nsim, and the name of the fitted model (model_CP) are included as object attributes.

See Also

cpm, rcp, ppersist