ljr0: MLE with 0 joinpoints

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/ljr0.R

Description

Determines the maximum likelihood estimate of model coefficients in the logistic joinpoint regression model with no joinpoints.

Usage

1
ljr0(y,n,tm,X,ofst)

Arguments

y

the vector of Binomial responses.

n

the vector of sizes for the Binomial random variables.

tm

the vector of observation times.

X

a design matrix containing other covariates.

ofst

a vector of known offsets for the logit of the response.

Details

The re-weighted log-likelihood is the log-likelihood divided by the largest component of n.

Value

Coef

A table of coefficient estimates.

wlik

The maximum value of the re-weighted log-likelihood.

Author(s)

The authors are Michal Czajkowski, Ryan Gill, and Greg Rempala. The software is maintained by Ryan Gill [email protected].

References

Czajkowski, M., Gill, R. and Rempala, G. (2008). Model selection in logistic joinpoint regression with applications to analyzing cohort mortality patterns. Statistics in Medicine 27, 1508-1526.

See Also

ljr01,ljrb,ljrf

Examples

1
2
3
 data(kcm)
 attach(kcm) 
 ljr0(Count,Population,Year+.5)

ljr documentation built on May 29, 2017, 10:22 a.m.