MCResultResampling.initialize {mcrPioda}

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,
  robust.cov = "MCD"
)

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

robust.cov

"MCD", "SDe" or "Classic" covariance method see rrcov

Value

No return value