nonprobsvy version 0.1.1

Version of the package submitted to CRAN

nonprobsvy 0.1.1

Bugfixes

• bug Fix occuring when estimation was based on auxiliary variable, which led to compression of the data from the frame to the vector.
• bug Fix related to not passing maxit argument from controlSel function to internally used nleqslv function
• bug Fix related to storing vector in model_frame when predicting y_hat in mass imputation glm model when X is based in one auxiliary variable only - fix provided converting it to data.frame object.

Features

• add information to summary about quality of estimation basing on difference between estimated and known total values of auxiliary variables
• add estimation of exact standard error for k-nearest neighbor estimator.
• add breaking change to controlOut function by switching values for predictive_match argument. From now on, the predictive_match = 1 means $\hat{y}-\hat{y}$ in predictive mean matching imputation and predictive_match = 2 corresponds to $\hat{y}-y$ matching.
• implement div option when variable selection (more in documentation) for doubly robust estimation.
• add more insights to nonprob output such as gradient, hessian and jacobian derived from IPW estimation for mle and gee methods when IPW or DR model executed.
• add estimated inclusion probabilities and its derivatives for probability and non-probability samples to nonprob output when IPW or DR model executed.
• add model_frame matrix data from probability sample used for mass imputation to nonprob when MI or DR model executed.

Unit tests

• added unit tests for variable selection models and mi estimation with vector of population totals available