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gmwm (version 2.0.0)

Generalized Method of Wavelet Moments

Description

Generalized Method of Wavelet Moments (GMWM) is an estimation technique for the parameters of time series models. It uses the wavelet variance in a moment matching approach that makes it particularly suitable for the estimation of certain state-space models. Furthermore, there exists a robust implementation of GMWM, which allows the robust estimation of some state-space models and ARIMA models. Lastly, the package provides the ability to quickly generate time series data, perform different wavelet decompositions, and visualizations.

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Install

install.packages('gmwm')

Monthly Downloads

29

Version

2.0.0

License

CC BY-NC-SA 4.0

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Pull Requests

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Repository

https://github.com/SMAC-Group/gmwm

Maintainer

Stephane Guerrier

Last Published

February 10th, 2016

Functions in gmwm (2.0.0)

Compute Theoretical ACF for an ARMA Process

Create an Autoregressive P [AR(P)] Process

ARMA process to WV approximation

Hook into R's ARIMA function

Create a Gauss-Markov (GM) Process

Create an Moving Average Q [MA(Q)] Process

ARMA process to WV

Converting an ARMA Process to an Infinite MA Process

all_bootstrapper

Bootstrap for Everything!

Plot the Wavelet Variances of IMU Object in Combined Type

Plot the Latent Time Series Graph

Generate eta3 confidence interval

batch_modwt_wvar_cpp

Computes the MO/DWT wavelet variance for multiple processes

Create an White Noise (WN) Process

AR1 process to WV

desc.to.ts.model

Create a ts.model from desc string

Generate a Demo about the Latent Time Series

autoplot.gmwmComp

Compare GMWM Model Fits with ggplot2 (Internal)

cust.model.score

Formats the model score matrix

Create an Random Walk (RW) Process

Calculate the Allan Variance

Analytic second derivative matrix for drift process

cov_bootstrapper

Bootstrap for Matrix V

Analytic D matrix of Processes

Print Maximum Overlap Discrete Wavelet Transform

Create Combination Matrix

Generate eta3 robust confidence interval

Find the auto imu result

Create an Autoregressive Moving Average (ARMA) Process

Absolute Value or Modulus of a Complex Number.

build_model_set

Build List of Unique Models

Generate the ts model object's theta vector

Retrieve GMWM starting value from Yannick's objective function

autoplot.wvar.imu

Plot the Wavelet Variances of IMU Object

Get the model in a gmwm object

Format the Confidence Interval for Estimates

Plot Time Series Data

Automatically select appropriate model for IMU

Haar filter construction

find_full_model

Find the Common Denominator of the Models

Transform AR1 to GM

gmwm_sd_bootstrapper

Bootstrap for Standard Deviations of Theta Estimates

Generate a drift

Generate the Confidence Interval for GOF Bootstrapped

Generate a random walk without drift

Graph Solution of the Generalized Method of Wavelet Moments Non-individually

Helper Function for ARMA to WV Approximation

Graphically Compare GMWM Models Constructed by the Same Data

Engine for obtaining the GMWM Estimator

Wrapper to Automatic Model Selection Results of IMU Object

Plot the Wavelet Variances of IMU Object in Split Type

Create a GMWM TS Object based on data

Compute Maximal-Overlap Allan Variance using Means

Generate Latent Time Series based on Model (Internal)

Removal of Boundary Wavelet Coefficients

Print gmwm object

Routing function for summary info

Generate a white noise process

Generate a sequence of values based on supplied number

gmwm_update_cpp

Update Wrapper for the GMWM Estimator

Frequent Graph Setting for Paper

Wrapper to Graph Solution of the Generalized Method of Wavelet Moments

Computes the (MODWT) wavelet variance

Print Wavelet Variances

select.desc.check

TS Model Checks

Graph Solution of the Generalized Method of Wavelet Moments for Each Process

compute_cov_cpp

Computes the (MODWT) wavelet covariance matrix

Time Series Convolution Filters

Create an Autoregressive 1 [AR(1)] Process

autoplot.auto.imu

Automatic Model Selection Results of IMU Object

Create a Wvar object

Computes the (MODWT) wavelet covariance matrix using Chi-square confidence interval bounds

Randomly guess starting parameters for ARMA

Check Invertibility Conditions

Create an Drift (DR) Process

Compute Tau-Overlap Allan Variance

Lagged Differences in Armadillo

Analytic D matrix for drift process

Generate an AR(1) sequence

Graph Solution of the Generalized Method of Wavelet Moments

Brickwall functionality for MO/DWT

ci_wave_variance

Generate a Confidence intervval for a Univariate Time Series

Compare Wavelet Variances

Compute the GOF Test

do_polyroot_arma

Root Finding C++

Discrete Fourier Transformation for Autocovariance Function

bootstrap_gof_test

Compute the Bootstrapped GoF Test

Graphically Compare GMWM Model Fit

Obtain the value of an object's properties

GMWM for Sensors, ARMA, SSM, and Robust

Discrete Wavelet Transform

Discrete Wavelet Transform

packageVersionCRAN

Latest Version of Package on CRAN

gmwm_master_cpp

Master Wrapper for the GMWM Estimator

Expected value DR

Analytic D matrix random walk process

Optim loses NaN

Analytic D matrix quantisation noise process

Create a GMWM TS Object based on model

Calculates the Jacobian for the ARMA process

gmwm_param_bootstrapper

Bootstrap for Estimating Both Theta and Theta SD

Order AR1s by size of phi.

Obtain the value of an object's properties

Emulate ggplot2 default color palette

Generate Latent Time Series Object Based on Data

opt_n_gof_bootstrapper

Bootstrap for Optimism and GoF

Mean of the First Difference of the Data

Read an IMU Binary File into R

derivative_first_matrix

Analytic D matrix of Processes

print.rank.models

Print function for rank.models object

Pseudo Logit Function

getObjFunStarting

Retrieve GMWM starting value from Yannick's objective function

model_process_desc

Generate the ts model object's process desc

decomp_to_theo_wv

Decomposed WV to Single WV

guess_initial_old

Randomly guess a starting parameter

Wrapper Function to Plot the Graph of Latent Time Series

Print function for auto.imu object

Quadrature Mirror Filter

Print Discrete Wavelet Transform

Reverse Armadillo Vector

GMWM for (Robust) Sensor

Automatically select appropriate model for a set of models

Obtain the smallest polynomial root

Generate a Wave Variance for a Univariate Time Series

Maximum Overlap Discrete Wavelet Transform

Find the Rank Models result

field_to_matrix

Transform an Armadillo field to a matrix

Wavelet Variance

Summary Allan Variance

Multiple a ts.model by constant

decomp_theoretical_wv

Each Models Process Decomposed to WV

optimism_bootstrapper

Bootstrap for Optimism

Predict future points in the time series using the solution of the Generalized Method of Wavelet Moments

Reverse Subset Row

Print Asymptotic Covariance Matrix

Subset an IMU Object

Second moment DR

Update GMWM object for sensor, ARMA, SSM, and Robust

untransform_values

Revert Transform Values for Display

autoplot.wvarComp

Detail Implementation to Compare Wavelet Variances

Calculate the Asymptotic Covariance Matrix

install_imudata

Install IMU Data Package

Logit Inverse Function

Order the Model

Update the Attributes of Objects

Generate the ts model object description

transform_values

Transform Values for Optimization

Generate Latent Time Series Object Based on Model

Generate the Confidence Interval for Theta Estimates

Convert Unit of Time Series Data

Update Object Attribute

Multiple a ts.model by constant

Indirect Inference for ARMA

print.summary.gmwm

Print summary.gmwm object

Wrapper to ggplot Wavelet Variances Graph

Generate a sequence of values

Wrapper Function to Plot the Wavelet Variances of IMU Object

Computes the (MODWT) wavelet variance

Plot Allan Variance

Time Series Recursive Filters

Formats the rank.models (auto.imu) object

Randomly guess starting parameters for AR1

Generate Time Series based on Model (Internal)

Logit2 Inverse Function

Generate a Quantisation Noise (QN) sequence

Plot Time Series Data

Quantisation Noise to WV

Computes the MODWT scales

Analytic D matrix white noise process

Randomly guess a starting parameter

Maximum Overlap Discrete Wavelet Transform

Print GMWM Data Object

Reverse Subset Column

Add ts.model objects together

Indirect Inference for ARMA

Read an IMU Binary File into R

Sort Matrix by Column

Model Process to WV

Summary of Wavelet Variances

Summary Maximum Overlap Discrete Wavelet Transform

White Noise to WV

Random Walk to WV

Summary Discrete Wavelet Transform

Select the Wavelet Filter

Summary of GMWM object

Conversion function of Vector to Set

ARMA Adapter to ARMA to WV Process function

Summary Wavelet Covariance Matrix

Accumulation of Armadillo field

Prints Allan Variance

summary.rank.models

Summary function for rank.models object

Mod_squared_cpp

Absolute Value or Modulus of a Complex Number Squared.

Create an Quantisation Noise (QN) Process

Graph Wavelet Variances

calculate_psi_matrix

Calculate the Psi matrix

Analytic second derivative matrix for AR(1) process

Analytic D matrix for AR(1) process

do_polyroot_cpp

Root Finding C++

Transform GM to AR1

Internal IMU Object Construction

Generalized Method of Wavelet Moments (GMWM) Package

Create an IMU Object

pseudo_logit_inv

Pseudo Logit Inverse Function

summary.auto.imu

Summary function for auto.imu object