# Individual foram approach uncertainty analysis in matlab

The following Matlab project contains the source code and Matlab examples used for individual foram approach uncertainty analysis . This code constructs synthetic time series with varying ENSO and seasonal cycle amplitudes for a point location in the tropical Pacific Ocean and produces a probability contour plot depending on the number of individual foraminfera analyzed.

# Harmonic analysis of time series using least squares fit. in matlab

The following Matlab project contains the source code and Matlab examples used for harmonic analysis of time series using least squares fit. . Returns amplitudes (C) and phases (pha) of the harmonic components of series, i*cos(2*pi*t/Ti-phai).

# Linear plot with multiple subplot and horizontal scrollbar for the inspection of long timeseries in matlab

The following Matlab project contains the source code and Matlab examples used for linear plot with multiple subplot and horizontal scrollbar for the inspection of long timeseries . scrollplot(dx, x1, y1, x2, y2, .

# Mackey glass time series forecasting using method 2 single stage fuzzy forecaster in matlab

The following Matlab project contains the source code and Matlab examples used for mackey glass time series forecasting using method 2 single stage fuzzy forecaster. Mackey-Glass Time Series Forecasting using Wang-Mendel Method

# Comparing time series using semblance analysis in matlab

The following Matlab project contains the source code and Matlab examples used for comparing time series using semblance analysis. Only in very simple situations can we describe the correlation between two time series as a single number.

# Multivariant kernel regression and smoothing in matlab

The following Matlab project contains the source code and Matlab examples used for multivariant kernel regression and smoothing. This function implements multivariant Gaussian kernel regression and smoothing.

# Semi variance method and scaled windowed variance method for fractal time series analysis. in matlab

The following Matlab project contains the source code and Matlab examples used for semi variance method and scaled windowed variance method for fractal time series analysis.. Semi variance method and scaled windowed variance method for fractal time series analysis.

# Wavelet based ms coherence estimator in matlab

The following Matlab project contains the source code and Matlab examples used for wavelet based ms coherence estimator. This function estimates and plots a wavelet-based magnitude-squared (MS) coherence between two time series and both sampled at the same sampling rate.

# Function to generate timeseries file to use for moore fsm coverage analysis. in matlab

The following Matlab project contains the source code and Matlab examples used for function to generate timeseries file to use for moore fsm coverage analysis.. This function generates a Timeseries file which can be used for Moore FSM coverage analysis.

# Fftnoise generate noise with a specified power spectrum in matlab

The following Matlab project contains the source code and Matlab examples used for fftnoise generate noise with a specified power spectrum. USAGE: noise=fftnoise(f[,Nseries])   INPUTS:   f: the fft of a time series (must be a column vector)   Nseries: number of noise series to generate.

# Mat2figure gui for browsing timeseries data easily in matlab

The following Matlab project contains the source code and Matlab examples used for mat2figure gui for browsing timeseries data easily. MAT2FIGURE allows you to review timeseries data contained in a matfile very fast and efficiently.

# Detrended fluctuation analysis in matlab

The following Matlab project contains the source code and Matlab examples used for detrended fluctuation analysis. it is consitent with the program provided by Oxford Univ www.

# Fast approximate entropy in matlab

The following Matlab project contains the source code and Matlab examples used for fast approximate entropy. Approximate Entropy (ApEn) is a popular tool in analysing the complexity of time series data especially in clinical research.

# Sample entropy in matlab

The following Matlab project contains the source code and Matlab examples used for sample entropy. 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.

# Temporal disaggregation library in matlab

The following Matlab project contains the source code and Matlab examples used for temporal disaggregation library. This library has been designed to perform temporal disaggregation of economic time series using a variety of techniques: univariate methods without indicators (Boot-Feibes-Lisman, Stram-Wei, low-pass interpolation), univariate methods with indicators (Denton, Chow-Lin, Fernandez, Litterman, Santos-Cardoso, Guerrero, Proietti) and multivariate methods with indicators and transversal constraints (Rossi, Denton, Di Fonzo).

# Permutation entropy in matlab

The following Matlab project contains the source code and Matlab examples used for permutation entropy. % Calculate the permutation entropy % Input: y: time series; % m: order of permuation entropy % t: delay time of permuation entropy, % Output: % pe: permuation entropy % hist: the histogram for the order distribution %Ref: G Ouyang, J Li, X Liu, X Li, Dynamic Characteristics of Absence EEG Recordings with Multiscale Permutation % % Entropy Analysis, Epilepsy Research, doi: 10.

# Multiscale permutation entropy (mpe) in matlab

The following Matlab project contains the source code and Matlab examples used for multiscale permutation entropy (mpe). % Calculate the Multiscale Permutation Entropy (MPE) % Input: X: time series; % m: order of permuation entropy % t: delay time of permuation entropy, % Scale: the scale factor % Output: % MPE: multiscale permuation entropy

# Temporal disaggregation library in matlab

The following Matlab project contains the source code and Matlab examples used for temporal disaggregation library. This library has been designed to perform temporal disaggregation of economic time series using a variety of techniques: univariate methods without indicators (Boot-Feibes-Lisman, Stram-Wei, low-pass interpolation), univariate methods with indicators (Denton, Chow-Lin, Fernandez, Litterman, Santos-Cardoso, Guerrero, Proietti) and multivariate methods with indicators and transversal constraints (Rossi, Denton, Di Fonzo).

# Spikegauss continuous firing rate time series from discrete spiketimes in matlab

The following Matlab project contains the source code and Matlab examples used for spikegauss continuous firing rate time series from discrete spiketimes.   Each spike is represented by a gaussian with maximum value 1 on the   timestamp.

# Noise variance estimation in matlab

The following Matlab project contains the source code and Matlab examples used for noise variance estimation. Suppose that you have a signal Y (Y can be a time series, a parametric surface or a volumetric data series) corrupted by a Gaussian noise with unknown variance.

# Faster plotting of large timeseries. in matlab

The following Matlab project contains the source code and Matlab examples used for faster plotting of large timeseries. . This function is a minimal wrapper for the matlab plot function with automatic downsampling at low zoom factors and cropping at high zoom factors for faster zooms and pans.

# Empirical orthogonal function (pca) estimation for eeg time series in matlab

The following Matlab project contains the source code and Matlab examples used for empirical orthogonal function (pca) estimation for eeg time series. This source contains the empirical orthogonal functional analysis (EOF) calculation for an individual or population of EEG power spectrum multivariate time series.

# Dissimilarity index based on order pattern analysis in matlab

The following Matlab project contains the source code and Matlab examples used for dissimilarity index based on order pattern analysis. % DsimOrder Calculate the Dissimilarity index based on order pattern analysis % % Input: X: 1xn time series; % Y: 1xm time series; % M: the embedding dimension (common M=3,4 or 5) % t: delay time of order pattern analysis, % % Output: % Dsim: Dissimilarity index between X and Y % PEx and PEy: permutation entropy of X and Y % Ref: Ouyang, G.

# Ar model in matlab

The following Matlab project contains the source code and Matlab examples used for ar model. LAMBDA = AR_MODEL(Y, N) estimates an N:th order autoregressive polynomial model (AR) for time series Y: y(t) + l_1 * y(t-1) + l_2 * y(t-2) + .

# Garch,egarch,nagarch,gjr models and implicit vix in matlab

The following Matlab project contains the source code and Matlab examples used for garch,egarch,nagarch,gjr models and implicit vix. The functions in this file can be used for estimate historical pararameters of GARCH/EGARCH/GJR/NAGARCH models using time series of prices, rates and CBOE VIX.

# Chaos test in matlab

The following Matlab project contains the source code and Matlab examples used for chaos test. This test performs the test for chaotic dynamics of a noisy time series based on the Lyapunov exponent.

# Easy 'n fast smoothing for 1 d to n d data in matlab

The following Matlab project contains the source code and Matlab examples used for easy 'n fast smoothing for 1 d to n d data. SMOOTHN provides a fast, unsupervised and robust discretized spline smoother for data of arbitrary dimension.

# Robust smoothing for 1 d to n d data (easy version of smoothn) in matlab

The following Matlab project contains the source code and Matlab examples used for robust smoothing for 1 d to n d data (easy version of smoothn). EZSMOOTHN provides a fast, automatized and robust discretized spline smoothing for real or complex data of arbitrary dimension.

# Low rank multivariate autoregressive model for dimensionality reduction in matlab

The following Matlab project contains the source code and Matlab examples used for low rank multivariate autoregressive model for dimensionality reduction. Despite the fact that they do not consider the temporal nature of data, classic dimensionality reduction techniques, such as PCA, are widely applied to time series data.

# Time series indexing in matlab

The following Matlab project contains the source code and Matlab examples used for time series indexing. Doing stimulus triggered averaging? Continuous EEG analysis? Want to know what the average hourly barometric pressures were for the last 30 years, but you need individual results for each month? A common problem in time series analysis is trying to get the average signal that follows (or precedes) a set of time points.

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