Other packages > Find by keyword >

SAutomata  

Inference and Learning in Stochastic Automata
View on CRAN: Click here


Download and install SAutomata package within the R console
Install from CRAN:
install.packages("SAutomata")

Install from Github:
library("remotes")
install_github("cran/SAutomata")

Install by package version:
library("remotes")
install_version("SAutomata", "0.1.0")



Attach the package and use:
library("SAutomata")
Maintained by
Muhammad Kashif Hanif
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-11-02
Latest Update: 2018-11-02
Description:
Machine learning provides algorithms that can learn from data and make inferences or predictions. Stochastic automata is a class of input/output devices which can model components. This work provides implementation an inference algorithm for stochastic automata which is similar to the Viterbi algorithm. Moreover, we specify a learning algorithm using the expectation-maximization technique and provide a more efficient implementation of the Baum-Welch algorithm for stochastic automata. This work is based on Inference and learning in stochastic automata was by Karl-Heinz Zimmermann(2017) .
How to cite:
Muhammad Kashif Hanif (2018). SAutomata: Inference and Learning in Stochastic Automata. R package version 0.1.0, https://cran.r-project.org/web/packages/SAutomata. Accessed 05 Aug. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited SAutomata R package
View SAutomata citation profile
Other R packages that SAutomata depends, imports, suggests or enhances
Complete documentation for SAutomata
Functions, R codes and Examples using the SAutomata R package
Some associated functions: BaumWelch . Sbackward . Sforward . TOC.sampleData . initSA . scores . 
Some associated R codes: BaumWelch.R . Sbackward.R . Sfoward.R . TOC.R . initSA.R . scores.R .  Full SAutomata package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

noisyr  
Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput sequencing data. Two approaches are use ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
kernelPSI  
Post-Selection Inference for Nonlinear Variable Selection
Different post-selection inference strategies for kernelselection as described in kernelPSI a Post-S ...
Download / Learn more Package Citations See dependency  
dcov  
A Fast Implementation of Distance Covariance
Efficient methods for computing distance covariance and relevant statistics. See Sz ...
Download / Learn more Package Citations See dependency  
dhReg  
Dynamic Harmonic Regression
Building and forecasting time series data with multiple seasonality using Dynamic Harmonic Regressio ...
Download / Learn more Package Citations See dependency  

28,083

R Packages

239,283

Dependencies

74,457

Author Associations

28,084

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA