NEWS.md

In itdr: Integral Transformation Methods for SDR in Regression

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News

Changes in itdr 2.0.1

• 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).

• Bug Fixes

• Fixed the errors in recumbent dataset.

Changes in itdr 2.0.0 (2023-06-23)

• 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

Changes in itdr 1.2.0 (2022-04-12)

• Enhancements

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

itdr 1.0.0 (2021-07-23)

• CRAN Initial Submission.
• GitHub Initial Submission.

itdr documentation built on May 29, 2024, 2:28 a.m.