ci {DDL} | R Documentation |
Computing confidence intervals
Description
generic function
Usage
ci(x, alpha = 0.05, alternative = c("two.sided", "less", "greater"))
Arguments
x |
An object of class |
alpha |
alpha Level of significance to construct confidence interval |
alternative |
indicates the alternative hypothesis to construct confidence interval and must be one of "two.sided" (default), "less", or "greater". |
Examples
index = 1
n=100
p=200
s=5
q=3
sigmaE=2
sigma=2
pert=1
H = pert*matrix(rnorm(n*q,mean=0,sd=1),n,q,byrow = TRUE)
Gamma = matrix(rnorm(q*p,mean=0,sd=1),q,p,byrow = TRUE)
#value of X independent from H
E = matrix(rnorm(n*p,mean=0,sd=sigmaE),n,p,byrow = TRUE)
#defined in eq. (2), high-dimensional measured covariates
X = E + H %*% Gamma
delta = matrix(rnorm(q*1,mean=0,sd=1),q,1,byrow = TRUE)
#px1 matrix, creates beta with 1s in the first s entries and the remaining p-s as 0s
beta = matrix(rep(c(1,0),times = c(s,p-s)),p,1,byrow = TRUE)
#nx1 matrix with values of mean 0 and SD of sigma, error in Y independent of X
nu = matrix(rnorm(n*1,mean=0,sd=sigma),n,1,byrow = TRUE)
#eq. (1), the response of the Structural Equation Model
Y = X %*% beta + H %*% delta + nu
result = DDL(X, Y, index)
# default alpha is 0.05
ci(result, alpha = 0.05)
ci(result, alpha = 0.05, alternative = "less")
ci(result, alpha = 0.05, alternative = "greater")
[Package DDL version 1.0.2 Index]