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  2. Polynomial regression - Wikipedia

    en.wikipedia.org/wiki/Polynomial_regression

    The polynomial regression model. can be expressed in matrix form in terms of a design matrix , a response vector , a parameter vector , and a vector of random errors. The i -th row of and will contain the x and y value for the i -th data sample. Then the model can be written as a system of linear equations : which when using pure matrix ...

  3. Local regression - Wikipedia

    en.wikipedia.org/wiki/Local_regression

    The LOESS curve approximates the original sine wave. Local regression or local polynomial regression, [1] also known as moving regression, [2] is a generalization of the moving average and polynomial regression. [3] Its most common methods, initially developed for scatterplot smoothing, are LOESS ( locally estimated scatterplot smoothing) and ...

  4. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    Linear trend estimation. Linear trend estimation is a statistical technique used to analyze data patterns. Data patterns, or trends, occur when the information gathered "tends" to increase or decrease over time. Linear trend estimation essentially creates a straight line on a graph of data that models the general direction that the data is heading.

  5. Trend-stationary process - Wikipedia

    en.wikipedia.org/wiki/Trend-stationary_process

    Trend-stationary process. In the statistical analysis of time series, a trend-stationary process is a stochastic process from which an underlying trend (function solely of time) can be removed, leaving a stationary process. [1] The trend does not have to be linear.

  6. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    A trend line could simply be drawn by eye through a set of data points, but more properly their position and slope is calculated using statistical techniques like linear regression. Trend lines typically are straight lines, although some variations use higher degree polynomials depending on the degree of curvature desired in the line.

  7. Coefficient of determination - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_determination

    In statistics, the coefficient of determination, denoted R2 or r2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable (s). It is a statistic used in the context of statistical models whose main purpose is either the prediction of future outcomes or the ...

  8. Quadratic growth - Wikipedia

    en.wikipedia.org/wiki/Quadratic_growth

    Quadratic growth. In mathematics, a function or sequence is said to exhibit quadratic growth when its values are proportional to the square of the function argument or sequence position. "Quadratic growth" often means more generally "quadratic growth in the limit ", as the argument or sequence position goes to infinity – in big Theta notation ...

  9. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    In statistics, simple linear regression (SLR) is a linear regression model with a single explanatory variable. That is, it concerns two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system) and finds a linear function (a non-vertical straight line) that, as accurately as possible, predicts ...