fngendata: Data generating function

Description

Generates data

Usage

fngendata(
  n,
  bin.k = 0,
  bin.prob = NULL,
  cont.k = 5,
  y.gen.bin.k = 0,
  y.gen.bin.beta = NULL,
  y.gen.bin.prob = NULL,
  y.gen.cont.beta = c(2, 4, 6, 8, 10),
  y.gen.cont.mod.k = 0,
  y.gen.cont.mod.beta = matrix(c(-2, 2), 1, 2, byrow = TRUE),
  y.gen.bin.mod.prob = c(0.5),
  y.gen.cont.sp.k = 0,
  y.gen.cont.sp.groups = 2,
  y.gen.cont.sp.rho = 0.2,
  y.gen.cont.sp.dif = 1,
  intercept.beta = 0,
  Xgenerator.method = "simstudy",
  corMatrix = 100,
  rho = NULL,
  corstr = NULL,
  condnumber = 1,
  mu = 0,
  muvect = NULL,
  sd = 1,
  sdvect = NULL,
  error.dist = "normal",
  error.dist.mean = 0,
  error.dist.sd = 1,
  error.dist.snr = NULL,
  error.dist.df = 2,
  dataframe = TRUE,
  seed = NULL
)

Value

A data.frame or a list composed of a matrix of independent variables values (X), a vector of the dependent variable values (y), a vector of coefficient values (coefficients), a vector of non-zero coefficients (y.coefficients), and a vector of the error values (epsilon).

Arguments

n: Number of individuals.
bin.k: Number of binary variables not used for generating y.
bin.prob: A vector of probabilities with length equal to bin.k.
cont.k: Number of continuous variables not used for generating y.
y.gen.bin.k: Number of binary variables used for generating y.
y.gen.bin.beta: A vector of coefficients with length equal to bin.k used to generate y.
y.gen.bin.prob: A vector of probabilities with length equal to y.gen.bin.k.
y.gen.cont.beta: A vector of coefficients with length equal to cont.k used to generate y.
y.gen.cont.mod.k: Experimental
y.gen.cont.mod.beta: Experimental
y.gen.bin.mod.prob: Experimental
y.gen.cont.sp.k: Experimental
y.gen.cont.sp.groups: Experimental
y.gen.cont.sp.rho: Experimental
y.gen.cont.sp.dif: Experimental
intercept.beta: Value for the constant used to generate y.
Xgenerator.method: Method used to generate X data ( "simstudy" or "svd").
corMatrix: A positive number for alphad (see rcorrmatrix), NULL or a correlation matrix to be used when Xgenerator is "simstudy".
rho: Correlation coefficient, -1 <= rho <= 1. Use when Xgenerator is "simstudy" and corMatrix is NULL.
corstr: correlation structure ("ind", "cs" or "ar1") (see genCorData) to be used when Xgenerator is "simstudy" and corMatrix is NULL.
condnumber: A value for the condition number of the X matrix to be used when Xgenerator is "svd".
mu: The mean of the variables. To be used when all variables have the same mean.
muvect: A vector of means. To be used when variables have different means. The length of muvect must be k.
sd: Standard deviation of the variables. To be used when all variables have the same standard deviation.
sdvect: A vector of standard deviations. To be used when variables have different standard deviations. The length of sdvect must be k.
error.dist: Distribution of the error. "normal" for normal distribution or "t" for t-student distribution.
error.dist.mean: Mean value used when error.dist is "normal".
error.dist.sd: Standard deviation value used when error.dist is "normal".
error.dist.snr: Signal to noise ratio. If not NULL, the value of error.dist.sd will be ignored and it will be determined accordingly.
error.dist.df: Degrees of freedom used when error.dist is "t".
dataframe: Logical. If TRUE, the default, returns a data.frame else returns a list.
seed: A seed for reproducibility.

Author

Jorge Cabral, jorgecabral@ua.pt

Examples

Run this code


dataGCEstim <- fngendata(
  n = 100, cont.k = 2,
  y.gen.cont.beta = c(3, 6, 9),
  intercept.beta = 1,
  Xgenerator.method = "svd", condnumber = 50,
  mu = 0, sd = 1,
  error.dist = "normal", error.dist.mean = 0, error.dist.snr = 5,
  dataframe = TRUE, seed = 230676)

summary(dataGCEstim)

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