Σ Statistical Analysis Help Save
We do all Master & PhD thesis statistics. Spss help & Free estimate.
www.EasyStatistics.co.uk (sponsored link)
 

SPSS Save
Services and software (including SPSS) for profiling and segmenting your customer base to maximise campaign value and optimise marketing channel.
www.tech4t.co.uk (sponsored link)
 

[web:reg] [free Excel Add-Ins (Hodrick Prescott, Bandpass, ADF, ARIMA, Correlogram...)] Save
My programs are primarily econometrical Excel Add-Ins which are written in VBA or C++. Add-Ins have the great advantage that you can work directly from Excel.
http://www.web-reg.de   

AlaVar Save
Freeware to compute the three Allan Standard Deviations of a time series.
http://yazdiet.club.fr/alavar.html   

Brodgar Save
Program package used for estimating common trends, seasonal components and cycles in short, non-stationary multivariate time series. Based on dynamic factor analysis.
http://www.brodgar.com/   

CaterpillarSSA Save
Based on the model-free method of time series analysis Caterpillar-SSA (Singular Spectrum Analysis). The result of the Caterpillar-SSA processing is identification, analysis and forecast of additive components of time series (trends, periodicities, noise). The program can be applied to multivariate analysis/forecasting and change-point detection.
http://www.gistatgroup.com/cat/   

DEMETRA Save
Free user-friendly interface to Tramo/Seats and X-12-Arima for automated applications and for detailed time series analysis.
http://forum.europa.eu.int/irc/dsis/e...   

JMulTi Save
Time series analysis program, written in Java, to accompany book "Applied Time Series Analysis", by Helmut Lutkepohl and Markus Kratzig.
http://www.jmulti.de   

Neuro: Dynamic Time Series Analysis Save
Features the visualization of the multi-channel, multi-frequency digitized data, discrimination, correlation analysis, spectrum, expected density and other functions.
http://www.geocities.com/somesoftware...   

kSpectra Toolkit Save
Using novel tools such as singular spectrum analysis and multitaper method, time series can be decomposed into noise and predictable components - trends and oscillatory modes, which can be reconstructed and forecasted.
http://www.spectraworks.com/   

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