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2. Linear regression - Wikipedia

   en.wikipedia.org/wiki/Linear_regression

   Linear quantile regression models a particular conditional quantile, for example the conditional median, as a linear function β T x of the predictors. Mixed models are widely used to analyze linear regression relationships involving dependent data when the dependencies have a known structure. Common applications of mixed models include ...

3. 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.

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. 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.

6. Fan chart (time series) - Wikipedia

   en.wikipedia.org/wiki/Fan_chart_(time_series)

   There are several ways to represent the forecast density depending on the shape of the forecasting distribution. If the forecast density is symmetric ( normal or Student's t , for instance), the fan centers at the mean (which coincides with the mode and median ) forecast, and the ranges expand like confidence intervals by adding and subtracting ...

7. 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 ...

8. RATS (software) - Wikipedia

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

   One advantage of RATS, as opposed to automated forecasting software, is that it is an actual programming language, which enables the user to design custom models, and change specifications. Recent versions have added report-generation tools designed to facilitate accurate exporting of results for use in papers and other documents.

9. Box–Jenkins method - Wikipedia

   en.wikipedia.org/wiki/Box–Jenkins_method

   The most common methods use maximum likelihood estimation or non-linear least-squares estimation. Statistical model checking by testing whether the estimated model conforms to the specifications of a stationary univariate process. In particular, the residuals should be independent of each other and constant in mean and variance over time.