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A Pascal program for weighted least squares regression on a microcomputer.

H Tyson, H Henderson, M McKenna

    Computer Programs in Biomedicine
    |October 1, 1982
    PubMed
    Summary
    This summary is machine-generated.

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    This study presents a fast, memory-efficient weighted least-squares regression program for microcomputers. The software efficiently handles large datasets and offers orthogonalization for robust parameter estimation.

    Area of Science:

    • Computational statistics
    • Microcomputer programming

    Background:

    • Weighted least-squares regression is a common statistical method.
    • Efficient implementation on microcomputers is crucial for accessibility.

    Purpose of the Study:

    • To develop a fast and memory-efficient weighted least-squares regression program for microcomputers.
    • To enable analysis of large datasets and provide orthogonalization capabilities.

    Main Methods:

    • Implementation in Pascal with Motorola 6809 assembler for machine-code generation.
    • Utilizes double precision for accuracy.
    • Program size is 22,000 bytes, allowing ample memory for large datasets.

    Main Results:

    • A regression with 72 observations and 24 parameters executes in 7 minutes.

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  • The program efficiently handles large data sets within microcomputer memory constraints.
  • Optional orthogonalization of the design matrix (X) is supported for improved parameter estimation and detection of linear dependencies.

    • Conclusions:

    • The developed program offers a practical and efficient solution for weighted least-squares regression on microcomputers.
    • Its features, including speed, memory efficiency, and orthogonalization, make it suitable for various statistical analyses.
    • The program's design allows for easy modification and compatibility with different Pascal compilers.