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  2. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/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 or is influenced by changes in an external factor.

  3. Confidence and prediction bands - Wikipedia

    en.wikipedia.org/wiki/Confidence_and_prediction...

    Confidence bands can be constructed around estimates of the empirical distribution function.Simple theory allows the construction of point-wise confidence intervals, but it is also possible to construct a simultaneous confidence band for the cumulative distribution function as a whole by inverting the Kolmogorov-Smirnov test, or by using non-parametric likelihood methods.

  4. Zero lag exponential moving average - Wikipedia

    en.wikipedia.org/wiki/Zero_lag_exponential...

    The formula for a given N-Day period and for a given data series is: [2] [3] = = + (()) = (,) The idea is do a regular exponential moving average (EMA) calculation but on a de-lagged data instead of doing it on the regular data.

  5. Extrapolation - Wikipedia

    en.wikipedia.org/wiki/Extrapolation

    Linear extrapolation means creating a tangent line at the end of the known data and extending it beyond that limit. Linear extrapolation will only provide good results when used to extend the graph of an approximately linear function or not too far beyond the known data.

  6. Romberg's method - Wikipedia

    en.wikipedia.org/wiki/Romberg's_method

    After trapezoid rule estimates are obtained, Richardson extrapolation is applied. For the first iteration the two piece and one piece estimates are used in the formula ⁠ 4 × (more accurate) − (less accurate) / 3 ⁠. The same formula is then used to compare the four piece and the two piece estimate, and likewise for the higher estimates

  7. Segmented regression - Wikipedia

    en.wikipedia.org/wiki/Segmented_regression

    The following statistical tests are used to determine the type of trend: significance of the breakpoint (BP) by expressing BP as a function of regression coefficients A 1 and A 2 and the means Y 1 and Y 2 of the y -data and the means X 1 and X 2 of the x data (left and right of BP), using the laws of propagation of errors in additions and ...

  8. Kernel (statistics) - Wikipedia

    en.wikipedia.org/wiki/Kernel_(statistics)

    The first requirement ensures that the method of kernel density estimation results in a probability density function. The second requirement ensures that the average of the corresponding distribution is equal to that of the sample used. If K is a kernel, then so is the function K* defined by K*(u) = λK(λu), where λ > 0. This can be used to ...

  9. Hodrick–Prescott filter - Wikipedia

    en.wikipedia.org/wiki/Hodrick–Prescott_filter

    The adjustment of the sensitivity of the trend to short-term fluctuations is achieved by modifying a multiplier . The filter was popularized in the field of economics in the 1990s by economists Robert J. Hodrick and Nobel Memorial Prize winner Edward C. Prescott , [ 1 ] though it was first proposed much earlier by E. T. Whittaker in 1923. [ 2 ]