MCResultResampling.initialize: Initialize Method for 'MCResultAnalytical' Objects.

Description

Method initializes newly created objects of class 'MCResultAnalytical'.

Usage

MCResultResampling.initialize(
  .Object,
  data = data.frame(X = NA, Y = NA),
  para = matrix(NA, ncol = 4, nrow = 2),
  xmean = 0,
  mnames = c("unknown", "unknown"),
  regmeth = "unknown",
  cimeth = "unknown",
  bootcimeth = "unknown",
  alpha = 0.05,
  glob.coef = c(0, 0),
  rng.seed = as.numeric(NA),
  rng.kind = "unknown",
  glob.sigma = c(0, 0),
  nsamples = 0,
  nnested = 0,
  B0 = 0,
  B1 = 0,
  MX = 0,
  sigmaB0 = 0,
  sigmaB1 = 0,
  error.ratio = 0,
  weight = 1
)

Value

No return value

Arguments

.Object: object to be initialized
data: empty data.frame
para: empty coefficient matrix
xmean: 0 for init-purpose
mnames: empty method names vector
regmeth: string specifying the regression-method
cimeth: string specifying the confidence interval method
bootcimeth: string specifying the method for bootstrap confidence intervals
alpha: value specifying the 100(1-alpha)% confidence-level
glob.coef: global coefficients
rng.seed: random number generator seed
rng.kind: type of the random number generator
glob.sigma: global sd values for regression parameters
nsamples: number of samples for resampling
nnested: number of inner simulation for nested bootstrap
B0: resampling intercepts
B1: resampling slopes
MX: Numeric vector with point estimations of (weighted-)average of reference method values for each bootstrap sample.
sigmaB0: SD for 'B0'
sigmaB1: SD for 'B1'
error.ratio: for deming regression
weight: 1 for each data point