New Features

Integrate all the multivariate sufficient dimension reduction methods in regression within the

*mitdr()*function.Integrate

*wh()*,*wx()*, and*wy()*functions into a single function*hyperPara()*.

Enhancements

- Integrate all the uni-variate sufficient dimension reduction methods in regression within the
*itdr()*function. The*itdr()*function now facilitate to use Fourier transformation method (FM), Convolution Transformation method (CM), Iterative hessian transformation method (iht), and inverse Fourier transformation method (invFM).

- Integrate all the uni-variate sufficient dimension reduction methods in regression within the
Bug Fixes

- Fixed the errors in
*recumbent*dataset.

- Fixed the errors in

New Features

Include the following integral transformation methods.

1). An iterated alternating direction method of multipliers (ADMM) algorithm that selects the sufficient variables using a Fourier transform sparse inverse regression estimators. This algorithm is integrated in

*admmft()*function.2). A Minimum Discrepancy Approach with Fourier Transform in Sufficient Dimension Reduction. This algorithm is integrated in

*fm_xire()*function.

Enhancements

Include the following data sets to the package.

1). prostate - The data describe the level of a prostate-specific antigen associated with eight clinical measures in 97 male patients taking a radical prostatectomy.

2). Raman - The Raman dataset contains 69 samples of fatty acid information in terms of percentage of total sample weight and percentage of total fat content

Enhancements

- Updated the package such that it matches with the R 4.2.0 upgrades.

**CRAN**Initial Submission.**GitHub**Initial Submission.