semimrGen {MixSemiRob}

Semiparametric Mixture Data Generator

Description

‘semimrGen’ is used to generate data for a two-component semiparametric mixture of regression models:

p m_1(x) + (1-p) m_2(x),

where m_1(x) = 4 -\sin(2\pi x) and m_2(x) = 1.5 + \cos(3\pi x). This function is used in the examples for the semimrLocal and semimrGlobal functions. See the examples for details.

Usage

semimrGen(n, p = 0.5, var = c(.1, .1), u)

Arguments

n

a scalar, specifying the number of observations in x.

p

a scalar, specifying the probability of an observation belonging to the first component, i.e., p in the model.

var

a vector of variances of observations for the two components.

u

a vector of grid points for x. If some specific explanatory variable are needed, create a vector and assign to u.

Value

A list containing the following elements:

x

vector of length n, which represents the explanatory variable that is randomly generated from Uniform(0,1).

y

vector of length n, which represent the response variable that is generated based on the mean functions m_1(x) and m_2(x), with the addition of normal errors having a mean of 0 and a standard deviation specified by the user.

true_mu

n by 2 matrix containing the values of m_1(x) and m_2(x) at x.

true_mu_u

length(u) by 2 matrix containing the values of m_1(x) and m_2(x) at u.

See Also

semimrLocal, semimrGlobal, semimrBinFull

Examples

n = 100
u = seq(from = 0, to = 1, length = 100)
true_p = c(0.3, 0.7)
true_var = c(0.09, 0.16)
out = semimrGen(n = n, p = true_p[1], var = true_var, u = u)