FFT.pat.optim: Optimizes the function 'logFFT.patients' using 'optim'...

In jasonxu90/bdsem: Analysis of discretely observed Birth-Death-Shift processes

Description

Function uses Nelder-Mead optimization as implemented in optim to maximize the log likelihood function logFFT.patients.

Usage

  FFT.pat.optim(betaInit, t.pat, num.patients, PATIENTDATA,
    patients.design, s1.seq, s2.seq, tol, max)

Arguments

betaInit	A vector, the initial guess for the algorithm
t.pat	A number, the observation interval length
num.patients	An integer, number of unique patients
PATIENTDATA	A matrix in the form returned by MakePatientData containing the set of observation intervals
patients.design	A design matrix in the same form as returned by PatientDesignExample
s1.seq	A vector of complex arguments evenly spaced along the unit circle
s2.seq	A vector of complex arguments evenly spaced along the unit circle
tol	A number for setting the relative tolerance for the algorithm (the reltol argument in optim)
max	An integer, the max number of iterations before termination

Details

Example code is not included here because of runtime; see vignette for tutorial on using this function.

Value

An optim type object

jasonxu90/bdsem documentation built on May 18, 2019, 5:54 p.m.