ipd (version 0.4.0)

pspa_y: PSPA M-Estimation for ML-predicted labels

Description

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
)

Value

A summary table presenting point estimates, standard error, confidence intervals (1 - alpha), P-values, and weights.

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".