Comparing Time Series

he code performs the simulation of time series with autoregressive fractionally integrated moving average (ARFIMA) models that generalize ARIMA (autoregressive integrated moving average) and ARMA autoregressive moving average models. ARFIMA models allow non-integer values of the differencing...

The code performs two tailed Mann-Kendall test modified to account for autocorrelation on the time series (Hamed and Rao, 1998).The null hypothesis of trend absence in the vector V is tested, against the alternative of trend. The result of the test is returned in H = 1 indicates a rejection of...

Approximate Entropy (ApEn) is a popular tool in analysing the complexity of time series data especially in clinical research.This function is a very simple and efficient implementation of ApEn, based on vectorization concept that improves speed tremendously over for-loop implementation.It also...


Platforms: Matlab

TICK2BAR[T,H,L,O,C,V]=Tick2Bar(t,p,v,g)Divides a time series into periods of g days(may be less than one day).It is useful in conjunction with HIGHLOW [T,H,L,O,C,V]=Tick2Bar(t,p,v,g); highlow(H(:),L(:),C(:),O(:),'k',T(:));It returns:T date/time of the periodH high of the periodL low of the...


Platforms: Matlab

computes the sample autocovariance of a time series x for lags from 0 to maxlag, returning a column vector of length maxlag+1. x must be a column vector having length m not less than maxlag+1. If no value is supplied for maxlag, the default is the minimum of m-1 and 100.


Platforms: Matlab

This technique simply calculates variation based on a comparison of all abundances in a time series, and is free of assumptions of an underlying 'normal' distribution. It is more robust that the coefficient of variation CV and/or the standard deviation of log transformed abundances SDL, it is not...


Platforms: Matlab

AMI computes and plots average mutual information (ami) and correlation of univariate or bivariate time series for different values of time lag.USAGE: [amis corrs] = ami(xy,nBins,nLags)INPUT: xy: either univariate (x) or bivariate ([x y]) time series data. If bivariate time series are given then...


Platforms: Matlab

ifilter(x,y) or ifilter(y) or ifilter([x y]) or ry=ifilter(x,y,center,width,shape,plotmode,filtermode)Keyboard-operated interactive Fourier filter function for time-series signal (x,y), with keyboard controls that allow you to adjust the filter parameters continuously while observing the effect...


Platforms: Matlab

[DIMENSION STANDARD_DEV] = fractalvol(DATA) calculates the fractal dimension of the 1 dimensional random walk, DATA. DATA is assumed to be a function of its indices. Finds fractal volatility by embedding in the unit square and box counting. Y axis will be rescaled values of DATA, x axis is...


Platforms: Matlab

It creates blocks of surrogate data with the same second order properties as the original time series dataset by transforming the original data into the frequency domain, randomizing the phases simultaneously across the time series and converting the data back into the time domain.


Platforms: Matlab

Techniques from information theory are usual for the selection of variables in time series prediction or pattern recognition. These tasks involve, directly or indirectly, the maximization of the mutual information between input and output data. However, this procedure requires a high...


Platforms: Matlab

This short code calculates the sample entropy (SampEn) of a given time series data. SampEn is a measure of complexity that can be easily applied to any type of time series data, including physiological data such as heart rate variability and EEG data.SampEn is conceptually similar to approximate...


Platforms: Matlab

The datafile represents 19 years of a cyclical data process with monthly output for month(i) of year y: output(i,y)The empirical means and standard deviations for month(i) are m(i) and s(i) respectivelyThe correlation between month(i) and month(i+1) is c(i+1). (Note: due to cyclical nature, c(i)...


Platforms: Matlab

Plots barbs or arrows conserving angles and can place a scaling bar.The positions of the components u and v can be entered as matrices or vectors as with quiver.m The x axes can be labels of datestr.m A scaling factor (dar) is used between the x axes and y axes to conserve the angles and another...


Platforms: Matlab

Shows y-values of time series in 2D plots by clicking on the axes.A quick test can be done by typingshowYs('example')after the file is placed in the Matlab pathIt works with one or multiple curves.By clicking repeatedly on different x positions, the labels and reference line come and go.After...


Platforms: Matlab

kSpectra Lite is a scientific application to introduce advanced time series analysis, and is a lite version of fully featured kSpectra app in App Store. kSpectra Lite provides a set of powerful tools for analysis of univariate or multivariate time series in various sciences, ranging from...


Platforms: Mac

OpenQuant is an open source backtesting and quantitative analysis platform for time series financial data. It offers a simple tradesystem development framework using open financial data from Yahoo.


Platforms: Mac

PresenTense Time Client is a network time client for Windows NT/2000/XP and 2003. It synchronizes your PC system clock to a network time server. Supports e-mail notification, redundancy and and can be remotely managed by LanTime Analyser. Windows NT/2000/XP/2003 version now supports NTP4 and...


Platforms: Windows

Perform statistical analysis on a Mac in the familiar environment. Turn Microsoft Excel 2004 or 2008 into a powerful statistical package with StatPlus:mac. Microsoft Excel provides invaluable calculation tools to Mac users. Its powerful features combined with ease of use made Microsoft...


Platforms: Mac

SSA generates a trayectory matrix from the original series by sliding a window of length L. The trayectory matrix is aproximated using Singular Value Decomposition. The last step reconstructs the series from the aproximated trayectory matrix. The SSA applications include smoothing, filtering, and...


Platforms: Matlab