pspa_y function conducts post-prediction M-Estimation.
Usage
pspa_y(
X_l = NA,
X_u = NA,
Y_l,
f_l,
f_u,
alpha = 0.05,
weights = NA,
quant = NA,
intercept = FALSE,
method
)Arguments
- X_l
Array or data.frame containing observed covariates in labeled data.
- X_u
Array or data.frame containing observed or predicted covariates in unlabeled data.
- Y_l
Array or data.frame of observed outcomes in labeled data.
- f_l
Array or data.frame of predicted outcomes in labeled data.
- f_u
Array or data.frame of predicted outcomes in unlabeled data.
- alpha
Specifies the confidence level as 1 - alpha for confidence intervals.
- weights
weights vector PSPA linear regression (d-dimensional, where d equals the number of covariates).
- quant
quantile for quantile estimation
- intercept
Boolean indicating if the input covariates' data contains the intercept (TRUE if the input data contains)
- method
indicates the method to be used for M-estimation. Options include "mean", "quantile", "ols", "logistic", and "poisson".