nbkal: Negative Binomial Models with Kalman Update

In swihart/repeated: Non-Normal Repeated Measurements Models

Negative Binomial Models with Kalman Update

Description

nbkal fits a negative binomial regression with Kalman update over time. The variance is proportional to the mean function, whereas, for kalcount with exponential intensity, it is a quadratic function of the mean.

Usage

nbkal(
  response,
  times,
  mu,
  preg,
  pdepend,
  kalman = TRUE,
  print.level = 0,
  ndigit = 10,
  gradtol = 1e-05,
  steptol = 1e-05,
  fscale = 1,
  iterlim = 100,
  typsize = abs(p),
  stepmax = 10 * sqrt(p %*% p)
)

Arguments

response	A list of two column matrices with counts and corresponding times for each individual, one matrix or dataframe of counts, or an object of class, response (created by restovec) or repeated (created by rmna or lvna).
times	When response is a matrix, a vector of possibly unequally spaced times when they are the same for all individuals or a matrix of times. Not necessary if equally spaced. Ignored if response has class, response or repeated.
mu	The mean function.
preg	The initial parameter estimates for the mean function.
pdepend	The estimates for the dependence parameters, either one or three.
kalman	If TRUE, fits the kalman update model, otherwise, a standard negative binomial distribution.
print.level	Arguments for nlm.
ndigit	Arguments for nlm.
gradtol	Arguments for nlm.
steptol	Arguments for nlm.
fscale	Arguments for nlm.
iterlim	Arguments for nlm.
typsize	Arguments for nlm.
stepmax	Arguments for nlm.

Details

Marginal and individual profiles can be plotted using mprofile and iprofile and residuals with plot.residuals.

Value

A list of classes nbkal and recursive is returned.

Author(s)

P. Lambert and J.K. Lindsey

References

Lambert, P. (1996) Applied Statistics 45, 31-38.

Lambert, P. (1996) Biometrics 52, 50-55.

Examples

y <- matrix(rnbinom(20,5,0.5), ncol=5)
times <- matrix(rep(seq(10,50,by=10),4), ncol=5, byrow=TRUE)
y0 <- matrix(rep(rnbinom(5,5,0.5),4), ncol=5, byrow=TRUE)
mu <- function(p) p[1]*log(y0)+(times<30)*p[2]*
	(times-30)+(times>30)*p[3]*(times-30)
nbkal(y, preg=c(1.3,0.008,-0.05), times=times, pdep=1.2, mu=mu)

swihart/repeated documentation built on Aug. 25, 2023, 12:34 p.m.