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  2. Linear least squares - Wikipedia

    en.wikipedia.org/wiki/Linear_least_squares

    Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems involved in linear regression, including variants for ordinary (unweighted), weighted, and generalized (correlated) residuals.

  3. Weighted least squares - Wikipedia

    en.wikipedia.org/wiki/Weighted_least_squares

    Weighted least squares (WLS), also known as weighted linear regression, [1] [2] is a generalization of ordinary least squares and linear regression in which knowledge of the unequal variance of observations (heteroscedasticity) is incorporated into the regression.

  4. Data Analysis Expressions - Wikipedia

    en.wikipedia.org/wiki/Data_Analysis_eXpressions

    Data Analysis Expressions (DAX) is the native formula and query language for Microsoft PowerPivot, Power BI Desktop and SQL Server Analysis Services (SSAS) Tabular models. DAX includes some of the functions that are used in Excel formulas with additional functions that are designed to work with relational data and perform dynamic aggregation .

  5. Reduced chi-squared statistic - Wikipedia

    en.wikipedia.org/wiki/Reduced_chi-squared_statistic

    In data analysis based on the Rasch model, the reduced chi-squared statistic is called the outfit mean-square statistic, and the information-weighted reduced chi-squared statistic is called the infit mean-square statistic.

  6. Non-linear least squares - Wikipedia

    en.wikipedia.org/wiki/Non-linear_least_squares

    Consider a set of data points, (,), (,), …, (,), and a curve (model function) ^ = (,), that in addition to the variable also depends on parameters, = (,, …,), with . It is desired to find the vector of parameters such that the curve fits best the given data in the least squares sense, that is, the sum of squares = = is minimized, where the residuals (in-sample prediction errors) r i are ...

  7. Weight function - Wikipedia

    en.wikipedia.org/wiki/Weight_function

    Weighted means are commonly used in statistics to compensate for the presence of bias.For a quantity measured multiple independent times with variance, the best estimate of the signal is obtained by averaging all the measurements with weight = /, and the resulting variance is smaller than each of the independent measurements = /.

  8. Unit-weighted regression - Wikipedia

    en.wikipedia.org/wiki/Unit-weighted_regression

    Unit-weighted regression is a method of robust regression that proceeds in three steps. First, predictors for the outcome of interest are selected; ideally, there should be good empirical or theoretical reasons for the selection.

  9. Microsoft Power BI - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Power_BI

    The first release of Power BI was based on the Microsoft Excel-based add-ins: Power Query, Power Pivot and Power View. With time, Microsoft also added many additional features like question and answers, enterprise-level data connectivity, and security options via Power BI Gateways. [ 10 ]