Interpolation & Prediction

Features Interpolation & Prediction

 The application is intended to interpolate real functions from a single variable.
Functions are a set of points (X, Y).
The following interpolation methods can be applied: Newtons, Aitkens, cubic Hermites method, cardinal spline interpolation, Catmul-Roms spline, Kochanek-Bartlss spline, linear interpolation and nearest neighbor interpolation.If the function is a time series, then methods for predicting and calculating autocorrelation may be applied to detect internal cycles.The following methods for statistical prediction are applied - an exponentially weighted moving average; - simple moving average; - linear exponential weighing; - Holts linear exponential smoothing; and an additional slowing trend.
The mean and the standard deviation of the forecast errors are calculated.The functions, the results of their processing and the forecasts can be stored in a database of type Sqlit or in selected folder .
Tables with this data can be exported for printing, for example, using the Sqlit browser or by Internet.
The application is intended to interpolate real functions from a single variable and for statistical predictioninterpolate real functions(set of points (X, Y)) from a single variablecan be applied interpolation methods: Newtons, Aitkens, cubic Hermites, cardinal splineCatmul-Roms spline, Kochanek-Bartlss spline, linear interpolation and nearest neighbor interpolation.can be applied statistical predictions - exponentially weighted moving average; - simple moving average; linear exponential weighing; - Holts linear exponential smoothing; and an additional slowing trend.results data can be exported and sending by Internet create, delete and selection of a folder for storage data results