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Showing results 1 to 10 of 2,496.


Function CCM_boot [multispatialCCM v1.0]
keywords
ts
title
Run multispatial CCM algorithm on two time series
description
Runs the multispatial convergent cross mapping algorithm on two time series, A and B, to determine whether process A is a forcing process (i.e., causally affects) or process B. A and B do not need to be from single, long time series, but rather can be combinations of many (e.g. spatially-replicated) time series. See "Arguments" for details.
Function make_ccm_data [multispatialCCM v1.0]
keywords
ts
title
Makes fake data for other functions
description
Builds a fake data set of two interacting processes, based on the model in the Sugihara et al. publication below, and based on a two-species discrete-time competition model. In the model, process A is causally affected by process B, but process B is not influenced by process A.
Function SSR_pred_boot [multispatialCCM v1.0]
keywords
ts
title
State space reconstruction function
description
Predict elements of A using B using state space reconstruction. If A=B, then the algorithm uses cross validation to assess the ability of historical portions of the A time series to predict future components of the time series. This function can be used to find the embedding dimension E that maximizes predictive ability.
Function SSR_check_signal [multispatialCCM v1.0]
keywords
ts
title
Test process for auto-predictability.
description
Predict elements of a process based historical observations of that process using cross-validation. Tests whether past observations are able to make good estimates of future elements of the time series.
Function ccmtest [multispatialCCM v1.0]
keywords
ts
title
Test for significant causal signal
description
Tests output from CCM_boot for significant causal signal. This function compares the 95% confidence intervals for esimated rho for the shortest and longest libraries calculated, and uses this to determine whether predictive power has significantly increased.
Function turnpoints [pastecs v1.3-18]
keywords
ts
title
Analyze turning points (peaks or pits)
description
Determine the number and the position of extrema (turning points, either peaks or pits) in a regular time series. Calculate the quantity of information associated to the observations in this series, according to Kendall's information theory
Function garsim [gsarima v0.1-4]
keywords
ts
title
Simulate a Generalized Autoregressive Time Series
description
Simulate a time series using a general autoregressive model.
Function arrep [gsarima v0.1-4]
keywords
ts
title
Compute the Autoregressive Representation of a Sarima Model
description
Invert (invertible) SARIMA(p, d, q, P, D, Q) models to ar representation.
Function lagPlot [gamlss.util v4.3-4]
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title
Lag plot for time series data
description
The function lagPlot() plots a time series variable against its lagged values or against the lagged values of an explanatory variable.
Function calc.trans [klaR v0.6-12]
keywords
ts
title
Calculation of transition probabilities
description
Function to estimate the probabilities of a time series to stay or change the state.