NEWS.md

In ipd: Inference on Predicted Data

ipd 0.1.3

• Added a NEWS.md file to track changes to the package.

• Added a pkgdown site for the package.

• ipd() now allows for regression through the origin with intercept = FALSE argument.

• ipd() now takes an additional argument, na_action, to handle missing covariate data.

• Currently supports "na.fail" and "na.omit". Defaults to na.fail.

• Provides a more informative error message and lists which covariates are missing observations.

• ipd() now takes an additional argument, n_t, which denotes the (optional) size of the training set used to generate the prediction rule. Defaults to Inf but is necessary for the postpi_X methods if n_t < n, N, the number of labeled and unlabeled observations, respectively, in the data being analyzed.

ipd 0.1.4

• Added a help topic for the package itself (man/ipd-package.Rd) via R/ipd-package.R and roxygen2

• Updated the documentation for ipd():

• Provided a more explicit description of the model argument, which is meant to specify the downstream inferential model or parameter to be estimated.

• Clarified that not all columns in data are used in prediction unless explicitly referenced in the formula argument or in the label argument if the data are passed as one stacked data frame.

• Updated the documentation for simdat() to include a more thorough explanation of how to simulate data with this function.

• simdat() now outputs a data.frame with a column named "set_label" instead of "set" to denote the labeled/unlabeled observation indicator.

ipd documentation built on April 4, 2025, 4:41 a.m.