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  2. Jamovi - Wikipedia

    en.wikipedia.org/wiki/Jamovi

    jamovi is an open source graphical user interface for the R programming language. [3] It is used in statistical research, especially as a tool for ANOVA (analysis of variance) and to understand statistical inference. [4] [5] It also can be used for linear regression, [6] mixed models and Bayesian models. [7]

  3. Stan (software) - Wikipedia

    en.wikipedia.org/wiki/Stan_(software)

    In addition, higher-level interfaces are provided with packages using Stan as backend, primarily in the R language: [4] rstanarm provides a drop-in replacement for frequentist models provided by base R and lme4 using the R formula syntax; brms [5] provides a wide array of linear and nonlinear models using the R formula syntax;

  4. Iteratively reweighted least squares - Wikipedia

    en.wikipedia.org/wiki/Iteratively_reweighted...

    IRLS is used to find the maximum likelihood estimates of a generalized linear model, and in robust regression to find an M-estimator, as a way of mitigating the influence of outliers in an otherwise normally-distributed data set, for example, by minimizing the least absolute errors rather than the least square errors.

  5. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    Linear regression is also a type of machine learning algorithm, more specifically a supervised algorithm, that learns from the labelled datasets and maps the data points to the most optimized linear functions that can be used for prediction on new datasets.

  6. R package - Wikipedia

    en.wikipedia.org/wiki/R_package

    R logo. R packages are extensions to the R statistical programming language.R packages contain code, data, and documentation in a standardised collection format that can be installed by users of R, typically via a centralised software repository such as CRAN (the Comprehensive R Archive Network).

  7. Least squares - Wikipedia

    en.wikipedia.org/wiki/Least_squares

    The result of fitting a set of data points with a quadratic function Conic fitting a set of points using least-squares approximation. In regression analysis, least squares is a parameter estimation method based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each ...

  8. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.

  9. Least-angle regression - Wikipedia

    en.wikipedia.org/wiki/Least-angle_regression

    In statistics, least-angle regression (LARS) is an algorithm for fitting linear regression models to high-dimensional data, developed by Bradley Efron, Trevor Hastie, Iain Johnstone and Robert Tibshirani. [1] Suppose we expect a response variable to be determined by a linear combination of a subset of potential covariates.