plsi.lr.v2: Partial linear single index linear regression for scalar...

In EPLSIM: Partial Linear Single Index Models for Environmental Mixture Analysis

Partial linear single index linear regression for scalar outcome, second version

Description

Partial linear single index linear regression for scalar outcome, second version

Usage

plsi.lr.v2(
  data,
  Y.name,
  X.name,
  Z.name,
  spline.num,
  spline.degree,
  initial.random.num,
  seed = 2026
)

Arguments

data	A data set including all needed variables
Y.name	Variable name for scalar outcome
X.name	Variable name vector for exposures
Z.name	Variable name vector for confounders
spline.num	A number representing the degree of freedom of B-spline basis for link function
spline.degree	A number representing the degree of the piece-wise polynomial of B-spline basis for link function
initial.random.num	A number representing the number of random initials used in the function
seed	A single integer used to seed the RNG so results (random initials and downstream optim() convergence) are reproducible. Set to NULL to skip seeding and use whatever RNG state is already active in the calling environment. Default is 2023.

Value

A list of model estimation and prediction results

Author(s)

Yuyan Wang

Examples

## Not run: 
data(nhanes.new)
data <- nhanes.new

Y.name <- "log.triglyceride"
X.name <- c("X1_trans.b.carotene", "X2_retinol", "X3_g.tocopherol", "X4_a.tocopherol",
            "X5_PCB99", "X6_PCB156", "X7_PCB206",
            "X8_3.3.4.4.5.pncb", "X9_1.2.3.4.7.8.hxcdf", "X10_2.3.4.6.7.8.hxcdf")
Z.name <- c("AGE.c", "SEX.Female", "RACE.NH.Black",
           "RACE.MexicanAmerican", "RACE.OtherRace", "RACE.Hispanic" )

spline.num <- 5
spline.degree <- 3
initial.random.num <- 1
seed = 2026

model_lr_v2 <- plsi.lr.v2(data = data, Y.name = Y.name, X.name = X.name, Z.name = Z.name,
                      spline.num, spline.degree, initial.random.num, seed = seed)

## End(Not run)

EPLSIM documentation built on Nov. 5, 2026, 1:08 a.m.