R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
tbma
View on CRAN: Click
here
Download and install tbma package within the R console
Install from CRAN:
install.packages("tbma")
Install from Github:
library("remotes")
install_github("cran/tbma") Install by package version:
library("remotes")
install_version("tbma", "0.1.0") Attach the package and use:
library("tbma")
Maintained by
Burakhan Sel
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-04-06
Latest Update:
Description:
We provide a forecasting model for time series forecasting problems with predictors. The offered model, which is based on a submitted research and called tree-based moving average (TBMA), is based on the integration of the moving average approach to tree-based ensemble approach. The tree-based ensemble models can capture the complex correlations between the predictors and response variable but lack in modelling time series components. The integration of the moving average approach to the tree-based ensemble approach helps the TBMA model to handle both correlations and autocorrelations in time series data. This package provides a tbma() forecasting function that utilizes the ranger() function from the 'ranger' package. With the help of the ranger() function, various types of tree-based ensemble models, such as extremely randomized trees and random forests, can be used in the TBMA model.
How to cite:
Burakhan Sel (2020). tbma: Tree-Based Moving Average Forecasting Model. R package version 0.1.0, https://cran.r-project.org/web/packages/tbma. Accessed 05 Aug. 2026.
Previous versions and publish date:
(2026-07-09 07:12), 0.1.0 (2020-04-06 16:20)
Other packages that cited tbma R package
View tbma citation profile
Other R packages that tbma depends,
imports, suggests or enhances
Functions, R codes and Examples using
the tbma R package
Some associated functions: tbma .
Some associated R codes: tbma.R . Full tbma package functions and examples
Downloads during the last 30 days
Today's Hot Picks in Authors and Packages
noisyr
Quantifies and removes technical noise from high-throughput
sequencing data. Two approaches are use ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Ilias Moutsopoulos (view profile)
kernelPSI
Different post-selection inference strategies for kernelselection as described in kernelPSI a Post-S ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Lotfi Slim (view profile)
quickcode
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
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
dhReg
Building and forecasting time series data with multiple seasonality using Dynamic Harmonic Regressio ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Pranay Gaikwad (view profile)
dcov
Efficient methods for computing distance covariance and relevant statistics. See Sz ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Hang Weiqiang (view profile)
28,083
R Packages
239,283
Dependencies
74,457
Author Associations
28,084
Publication Badges
