preproglucacon

Sequence of bases for preproglucacon DNA protein

datasets

Functions and S4 methods to create and manage discrete time Markov
chains more easily. In addition functions to perform statistical (fitting
and drawing random variates) and probabilistic (analysis of their structural
proprieties) analysis are provided. See Spedicato (2017) <doi:10.32614/RJ-2017-036>.
Some functions for continuous times Markov chains depends on the suggested ctmcd package, that,
as May 2023, can be retrieved from <https://cran.r-project.org/src/contrib/Archive/ctmcd/ctmcd_1.4.2.tar.gz>.

Giorgio Spedicato

markovchain

Easy Handling Discrete Time Markov Chains

Giorgio Alfredo Spedicato

Tae Seung Kang

Sai Bhargav Yalamanchi

Mildenberger Thoralf

Deepak Yadav

Ignacio Cordón

Vandit Jain

Toni Giorgino

Richèl J.C. Bilderbeek

Daniel Ebbert

Shreyash Maheshwari

preproglucacon function

A data frame with 1572 observations on the following 2 variables.<dl>
 <dt><code>V1</code></dt>
<dd>a numeric vector, showing original coding</dd> <dt><code>preproglucacon</code></dt>
<dd>a character vector, showing initial of DNA bases (Adenine, Cytosine, Guanine, Thymine)</dd>
</dl>

Format

Preprogluccacon DNA protein bases sequences — preproglucacon

A data frame with 1572 observations on the following 2 variables.<dl>
 <dt><code>V1</code></dt>
<dd>a numeric vector, showing original coding</dd>

 <dt><code>preproglucacon</code></dt>
<dd>a character vector, showing initial of DNA bases (Adenine, Cytosine, Guanine, Thymine)</dd>


</dl>

Preprogluccacon DNA protein bases sequences

preproglucacon: Preprogluccacon DNA protein bases sequences

Description

Usage

Arguments

Format

References

Examples