Reversible jump step for removing the breakpoints

reversibleJumpBreakPointsRemove(
  res,
  currentSigma,
  currentb,
  currentpi,
  currentq,
  currentd,
  currentbp,
  logmean = 0,
  logsd = 1,
  shape = 1,
  rate = 5,
  shape1 = 1,
  shape2 = 5,
  pishape1 = 1,
  pishape2 = 1,
  dshape = 1,
  drate = 1,
  K,
  R,
  rho,
  lambda,
  multivariate = FALSE,
  cormat = cormat,
  timepoints = timepoints,
  tCoef,
  index,
  numExch,
  density,
  phi
)

Arguments

res: data frame of uptake data
currentSigma: numeric current variance parameter
currentb: numeric vector of current rate parameters
currentpi: numeric vector of current mixing parameters
currentq: numeric vector of current stretch parameters
currentd: numeric vector of current rate parameters
currentbp: numeric vector of current breakpoints
logmean: numeric mean of the prior lognormal distribution
logsd: numeric standard deviation of the prior lognormal distribution
shape: numeric shape parameter of the prior gamma distribution
rate: numeric rate parameter of the prior gamma distribution
shape1: numeric shape parameter of the prior beta distribution
shape2: numeric shape parameter of the prior beta distribution
pishape1: numeric shape parameter of the prior beta distribution
pishape2: numeric shape parameter of the prior beta distribution
dshape: numeric shape parameter of the prior gamma distribution
drate: numeric rate parameter of the prior gamma distribution
K: numeric number of breakpoints
R: numeric maximum value of the breakpoints
rho: numeric probability of adding a breakpoint
lambda: numeric the mean number of break points
multivariate: logical flag for multivariate model
cormat: numeric correlation matrix
timepoints: numeric vector of time points
tCoef: numeric vector of scaling variance of time points
index: list of indices for each peptide residues
numExch: list of number of exchangeable amides for each peptide
density: character string of density function
phi: numeric maximum uptake possible

Value

list of updated parameters