coefficients-methods: coefficients method

In fmrs: Variable Selection in Finite Mixture of AFT Regression and FMR

Description

Provides the estimated regression coefficients from the fitted FMRs model from an fmrsfit-class

Usage

coefficients(object, ...)

## S4 method for signature 'fmrsfit'
coefficients(object, ...)

Arguments

object	An fmrsfit-class
...	Other possible arguments

Value

A numeric array of dimension-(nCov+1)-nComp

Author(s)

Farhad Shokoohi <[e-mail]>

Examples

set.seed(1980)
nComp = 2
nCov = 10
nObs = 500
dispersion = c(1, 1)
mixProp = c(0.4, 0.6)
rho = 0.5
coeff1 = c( 2,  2, -1, -2, 1, 2, 0, 0,  0, 0,  0)
coeff2 = c(-1, -1,  1,  2, 0, 0, 0, 0, -1, 2, -2)
umax = 40

dat <- fmrs.gendata(nObs = nObs, nComp = nComp, nCov = nCov,
                     coeff = c(coeff1, coeff2), dispersion = dispersion,
                     mixProp = mixProp, rho = rho, umax = umax,
                     disFamily = "lnorm")

res.mle <- fmrs.mle(y = dat$y, x = dat$x, delta = dat$delta,
                   nComp = nComp, disFamily = "lnorm",
                   initCoeff = rnorm(nComp*nCov+nComp),
                   initDispersion = rep(1, nComp),
                   initmixProp = rep(1/nComp, nComp))
coefficients(res.mle)

Example output

BugReports: https://github.com/shokoohi/fmrs/issues
                Comp.1      Comp.2
Intercept -1.010975273  2.82959558
X.1       -1.074208790  2.56118390
X.2        0.867308469 -1.24041307
X.3        2.061871052 -2.67969891
X.4        0.131998889  1.26462647
X.5       -0.006089305  2.41814396
X.6        0.036982382 -0.05336862
X.7       -0.130526357  0.25919575
X.8       -1.014279759 -0.15152879
X.9        1.981844440  0.04088745
X.10      -1.994586445  0.10757633

fmrs documentation built on May 2, 2019, 4:18 a.m.