expect.phi: Expectation of basis functions

In drtagkim/mcgillfdar: Functional Data Analysis

Description

Computes expectations of basis functions with respect to a density by numerical integration using Romberg integration

Usage

normint.phi(basisobj, cvec, JMAX=15, EPS=1e-7)
normden.phi(basisobj, cvec, JMAX=15, EPS=1e-7)
expect.phi(basisobj, cvec, nderiv=0, rng=rangeval,
                     JMAX=15, EPS=1e-7)
expectden.phi(basisobj, cvec, Cval=1, nderiv=0, rng=rangeval,
                     JMAX=15, EPS=1e-7)
expectden.phiphit(basisobj, cvec, Cval=1, nderiv1=0,
                 nderiv2=0, rng=rangeval, JMAX=15, EPS=1e-7)

Arguments

basisobj	a basis function object
cvec	coefficient vector defining density, of length NBASIS
Cval	normalizing constant defining density
nderiv, nderiv1, nderiv2	order of derivative required for basis function expectation
rng	a vector of length 2 giving the interval over which the integration is to take place
JMAX	maximum number of allowable iterations
EPS	convergence criterion for relative stop

Details

normint.phi computes integrals of p(x) = exp phi'(x)

normdel.phi computes integrals of p(x) = exp phi"(x)

expect.phi computes expectations of basis functions with respect to intensity p(x) <- exp t(c)*phi(x)

expectden.phi computes expectations of basis functions with respect to density

p(x) <- exp(t(c)*phi(x))/Cval

expectden.phiphit computes expectations of cross product of basis functions with respect to density

p(x) <- exp(t(c)*phi(x))/Cval

Value

A vector SS of length NBASIS of integrals of functions.

See Also

plot.basisfd,

drtagkim/mcgillfdar documentation built on May 12, 2019, 6:20 p.m.