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  2. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    Bayesian linear regression applies the framework of Bayesian statistics to linear regression. (See also Bayesian multivariate linear regression .) In particular, the regression coefficients β are assumed to be random variables with a specified prior distribution .

  3. RATS (software) - Wikipedia

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

    All these methods can be used in order to forecast, as well as to conduct data analysis. In addition, RATS can handle cross-sectional and panel data: Linear regression, including stepwise. Regressions with heteroscedasticity and serial-correlation correction. Non-linear least squares.

  4. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    In linear regression, the model specification is that the dependent variable, is a linear combination of the parameters (but need not be linear in the independent variables). For example, in simple linear regression for modeling n {\displaystyle n} data points there is one independent variable: x i {\displaystyle x_{i}} , and two parameters, β ...

  5. The Complete Guide to Trend-Following Indicators

    www.aol.com/news/complete-guide-trend-following...

    Time Series Forecast – uses linear regression to identify divergences between current price and the expected mean. It is constructed to be more flexible than basic linear regression analysis.

  6. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    This is a clear trend. ANOVA gives p = 0.091, because the overall variance exceeds the means, whereas linear trend estimation gives p = 0.012. However, should the data have been collected at four time points in the same individuals, linear trend estimation would be inappropriate, and a two-way (repeated measures) ANOVA would have been applied.

  7. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    It is a measure used to evaluate the performance of regression or forecasting models. It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume). [3]

  8. Ordinary least squares - Wikipedia

    en.wikipedia.org/wiki/Ordinary_least_squares

    In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression model (with fixed level-one [clarification needed] effects of a linear function of a set of explanatory variables) by the principle of least squares: minimizing the sum of the squares of the differences between the observed dependent variable (values ...

  9. Trend analysis - Wikipedia

    en.wikipedia.org/wiki/Trend_analysis

    If the trend can be assumed to be linear, trend analysis can be undertaken within a formal regression analysis, as described in Trend estimation. If the trends have other shapes than linear, trend testing can be done by non-parametric methods, e.g. Mann-Kendall test, which is a version of Kendall rank correlation coefficient.

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