Package: simts 0.2.2

Stéphane Guerrier

simts: Time Series Analysis Tools

A system contains easy-to-use tools as a support for time series analysis courses. In particular, it incorporates a technique called Generalized Method of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust parameter estimation of time series models which is described, for example, in Guerrier et al. (2013) <doi:10.1080/01621459.2013.799920>. More details can also be found in the paper linked to via the URL below.

Authors:Stéphane Guerrier [aut, cre, cph], James Balamuta [aut, cph], Roberto Molinari [aut, cph], Justin Lee [aut], Lionel Voirol [aut], Yuming Zhang [aut], Wenchao Yang [ctb], Nathanael Claussen [ctb], Yunxiang Zhang [ctb], Christian Gunning [cph], Romain Francois [cph], Ross Ihaka [cph], R Core Team [cph]

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simts.pdf |simts.html✨
simts/json (API)
NEWS

# Install 'simts' in R:
install.packages('simts', repos = c('https://smac-group.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/smac-group/simts/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • australia - Quarterly Increase in Stocks Non-Farm Total, Australia
  • hydro - Mean Monthly Precipitation, from 1907 to 1972
  • savingrt - Personal Saving Rate

On CRAN:

rcpprcpparmadillosimulationtime-seriestimeseriestimeseries-dataopenblascpp

7.68 score 15 stars 4 packages 59 scripts 231 downloads 1 mentions 91 exports 33 dependencies

Last updated 1 years agofrom:95709572c9. Checks:4 OK, 7 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 08 2025
R-4.5-win-x86_64NOTEFeb 08 2025
R-4.5-mac-x86_64NOTEFeb 08 2025
R-4.5-mac-aarch64NOTEFeb 08 2025
R-4.5-linux-x86_64NOTEFeb 08 2025
R-4.4-win-x86_64NOTEFeb 09 2025
R-4.4-mac-x86_64NOTEFeb 08 2025
R-4.4-mac-aarch64NOTEFeb 08 2025
R-4.3-win-x86_64OKFeb 09 2025
R-4.3-mac-x86_64OKFeb 08 2025
R-4.3-mac-aarch64OKFeb 08 2025

Exports:ARAR1ar1_to_gmARIMAARMAARMA11auto_corrbest_modelcheckcombcompare_acfconv.ar1.to.gmconv.gm.to.ar1corr_analysiscreate_imudesc.to.ts.modeldiag_boxpiercediag_ljungboxDRestimateevaluateFGNgen_ar1gen_ar1blocksgen_arimagen_armagen_arma11gen_bigen_drgen_fgngen_generic_sarimagen_gtsgen_ltsgen_lts_cppgen_ma1gen_materngen_meangen_modelgen_nswngen_powerlawgen_qngen_rwgen_sarimagen_sarmagen_singen_wnGMgm_to_ar1gmwmgmwm_master_cppgtsgts_timehasimuis.gtsis.imuis.ltsis.ts.modelis.wholeltsMMAMa_cppMa_cpp_vecMA1make_frameMAPEMATmodel_objdescmodel_process_descmodel_thetanp_boot_sd_medorderModelPLPQNRWRW2dimensionSARIMASARMAselectselect_arselect_arimaselect_armaselect_maSINtheo_acftheo_pacfunitConversionupdate_objvalueWN

Dependencies:backportsbroomclicolorspacecpp11dplyrfansifarvergenericsgluelabelinglifecyclemagrittrmunsellpillarpkgconfigpurrrR6RColorBrewerRcppRcppArmadillorlangrobcorscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

simts Vignettes

Rendered fromvignettes.Rmdusingknitr::rmarkdownon Feb 08 2025.

Last update: 2022-09-02
Started: 2017-09-08

Readme and manuals

Help Manual

Help pageTopics
Subset an IMU Object[.imu
Akaike's Information CriterionAIC.fitsimts
Create an Autoregressive P [AR(P)] ProcessAR
Definition of an Autoregressive Process of Order 1AR1
AR(1) process to WVar1_to_wv
Create an Autoregressive Integrated Moving Average (ARIMA) ProcessARIMA
Create an Autoregressive Moving Average (ARMA) ProcessARMA
ARMA process to WVarma_to_wv
Definition of an ARMA(1,1)ARMA11
ARMA(1,1) to WVarma11_to_wv
Quarterly Increase in Stocks Non-Farm Total, Australiaaustralia
Empirical ACF and PACFauto_corr
Select the Best Modelbest_model
Diagnostics on Fitted Time Series Modelcheck
Comparison of Classical and Robust Correlation Analysis Functionscompare_acf
Correlation Analysis Functionscorr_analysis
Analytic second derivative matrix for AR(1) processderiv_2nd_ar1
Analytic D matrix for ARMA(1,1) processderiv_2nd_arma11
Analytic second derivative matrix for drift processderiv_2nd_dr
Analytic second derivative for MA(1) processderiv_2nd_ma1
Analytic D matrix for AR(1) processderiv_ar1
Analytic D matrix for ARMA(1,1) processderiv_arma11
Analytic D matrix for Drift (DR) Processderiv_dr
Analytic D matrix for MA(1) processderiv_ma1
Analytic D matrix for Quantization Noise (QN) Processderiv_qn
Analytic D matrix Random Walk (RW) Processderiv_rw
Analytic D Matrix for a Gaussian White Noise (WN) Processderiv_wn
Analytic D matrix of Processesderivative_first_matrix
Box-Piercediag_boxpierce
Ljung-Boxdiag_ljungbox
Diagnostic Plot of Residualsdiag_plot
Portmanteau Testsdiag_portmanteau_
Create an Drift (DR) ProcessDR
Drift to WVdr_to_wv
Fit a Time Series Model to Dataestimate
Evalute a time series or a list of time series modelsevaluate
Definition of a Fractional Gaussian Noise (FGN) ProcessFGN
Generate AR(1) Block Processgen_ar1blocks
Generate Bias-Instability Processgen_bi
Simulate a simts TS object using a theoretical modelgen_gts
Generate a Latent Time Series Object Based on a Modelgen_lts
Generate Non-Stationary White Noise Processgen_nswn
Create a Gauss-Markov (GM) ProcessGM
Generalized Method of Wavelet Moments (GMWM)gmwm
GMWM for (Robust) Inertial Measurement Units (IMUs)gmwm_imu
Create a simts TS object using time series datagts
Mean Monthly Precipitation, from 1907 to 1972hydro
Create an IMU Objectimu
Pulls the IMU time from the IMU objectimu_time
Is simts Objectis.gts is.imu is.lts is.ts.model
Generate a Latent Time Series Object from Datalts
Definition of a Mean deterministic vector returned by the matrix by vector product of matrix X and vector betaM
Create an Moving Average Q [MA(Q)] ProcessMA
Definition of an Moving Average Process of Order 1MA1
Moving Average Order 1 (MA(1)) to WVma1_to_wv
Default utility function for various plots titlesmake_frame
Median Absolute Prediction ErrorMAPE
Definition of a Matérn ProcessMAT
Bootstrap standard error for the mediannp_boot_sd_med
Plot Time Series Forecast Functionplot_pred
Plot the GMWM with the Wavelet Varianceplot.gmwm
Plot Partial Auto-Covariance and Correlation Functionsplot.PACF
Plot Auto-Covariance and Correlation Functionsplot.simtsACF
Definition of a Power Law ProcessPLP
Time Series Predictionpredict.fitsimts
Predict future points in the time series using the solution of the Generalized Method of Wavelet Momentspredict.gmwm
Create an Quantisation Noise (QN) ProcessQN
Quantisation Noise (QN) to WVqn_to_wv
Read an IMU Binary File into Rread.imu
Plot the Distribution of (Standardized) Residualsresid_plot
GMWM for Robust/Classical Comparisonrgmwm
Truncated Normal Distribution Sampling Algorithmrtruncated_normal
Create an Random Walk (RW) ProcessRW
Random Walk to WVrw_to_wv
Function to Compute Direction Random Walk MovesRW2dimension
Create a Seasonal Autoregressive Integrated Moving Average (SARIMA) ProcessSARIMA
Create a Seasonal Autoregressive Moving Average (SARMA) ProcessSARMA
Personal Saving Ratesavingrt
Time Series Model Selectionselect
Run Model Selection Criteria on ARIMA Modelsselect_ar select_arima select_arma select_ma
Basic Diagnostic Plot of Residualssimple_diag_plot
Simplify and print SARIMA modelsimplified_print_SARIMA
Definition of a Sinusoidal (SIN) ProcessSIN
Summary of fitsimts objectsummary.fitsimts
Summary of GMWM objectsummary.gmwm
Theoretical Autocorrelation (ACF) of an ARMA processtheo_acf
Theoretical Partial Autocorrelation (PACF) of an ARMA processtheo_pacf
Update (Robust) GMWM object for IMU or SSMupdate.gmwm
Update Object Attributeupdate.gts update.imu update.lts
Obtain the value of an object's propertiesvalue value.imu
Create an White Noise (WN) ProcessWN
Gaussian White Noise to WVwn_to_wv