:exclamation: This is a read-only mirror of the CRAN R package repository. mbsts — Multivariate Bayesian Structural Time Series
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Functions and analyses to illustrate the performance of correction methods that allow averaging correlation coefficients.
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Implements the multivariate time series break detection of Bai, Lumsdaine and Stock (1998)
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Time Series Data on the 2019 Parliamentary Elections in Portugal
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R package consisting of functions and tools to facilitate the use of traditional time series and machine learning models to generate forecasts on univariate or multvariate data. Different backtesting scenarios are available to identify the best performing models.
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Practicing Time Series Analysis.
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R package for sensitivity analysis method in causal inference based on Tukey's Factorization
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Predict Electricity load from historical time series
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Prints OHLC time series with style
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An R package for modelling periodically correlated and periodically integrated time series
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Supporting code for the manuscript "Deep learning for clustering of multivariate clinical patient trajectories with missing values"
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Grocery_items_time-series_demands_forecastingby sushil1792
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License: No License (No License)#ARIMA #PROPHET #ETS #XGBOOST In this study, I developed and compared the performance of time-series prediction algorithms such as ARIMA, ETS and PROPHET for forecasting demand of Grocery items for a retail store chain in Ecuador
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This is the R code used to analyse the data for paper "Opportunities to reduce antibiotic prescribing for patients with COPD in primary care"
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ARIMA modelling
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Trend Analysis Using Innovative Trend Analysis Method and Change Point Analysis Using Seqential Mann-Kendall Plot and Distribution Free Cumulative Sum Plot
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Time-Series-Analysis-and-Forecastingby parthakuila
R 2 Version:Current License: No License (No License)
License: No License (No License)Build time series modelling and evaluation the best model. Build model like ARIMA, Exponential Smoothing, TBATS, NN and others. Compare the best model forecast the next 30 , 60 data points.
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An R port of the Multivariate Time Series Forecasting with Keras blog post
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Hunsinger_StochasticForecastby AppliedDemogToolbox
R 2 Version:Current License: No License (No License)
License: No License (No License)Eddie's Stochastic Population Forecast Code
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Download and Model Stock Index Constituents From Yahoo Finance
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Time-series modeling with catboost ( R Ver. )
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Part 3 of my Building Breather series. https://github.com/alexbaramilis/Building-Breather
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Part 1 of my Building Breather series. https://github.com/alexbaramilis/Building-Breather
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R 2 Version:Current License: No License (No License)
License: No License (No License)Stock Price Prediction using ARIMA model with Fourier Series
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Time Series structural break analysis using Bai-Perron method
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Matlab and R routines to robustly estimate open ocean CO2 variables and macronutrients from T, S and O2 data using Bayesian neural networks ("CANYON-B") of Bittig et al. (2018) Front. Mar. Sci. 5:328. http://dx.doi.org/10.3389/fmars.2018.00328
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:package: Package containing functions for ecological model used in disturbance ecology series
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Time series forecasting with linear regression and machine learning methods
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Scripts and reference data for accessing GIS and Time series servers
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Time series prediction system in R (RStudio) for given real-time e-commerce dataset of thousands of products, customers, and categories with the help of data mining algorithms (ARIMA, Holt Winter, STL, ETS).
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R 2 Version:Current License: No License (No License)
License: No License (No License)"Evaluation procedures for forecasting with spatio-temporal data" -- ECML 2018
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Using Bayesian Structural Time Series to empirically test the Kanye Conjecture
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R version of the stealBasis financial time series analysis project.
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Sensor performance analysis in the battleVerse
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Model for estimating return periods for flood events
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Time series data from http://www.comp-engine.org/
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General purpose timeseries database
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a set of functions to compute solar irradiance under clear sky conditions
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Testing for and Detecting Stuctural Breaks in Time Series Data
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Code for the chapter "Iterated filtering methods for Markov process epidemic models"
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Based on a series of articles by Nicolas Roard Medium
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Methods for aggregating p-values
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Non-parametric Mann-Kendall trend tests
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Correlation-based approach for identification of endocrine interactions
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R package for fitting a suite equations for the unimodal response to temperature
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R/tstmle01: Estimation and Inference for Marginal Causal Effect with Single Binary Time Series
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Finding communities in a bipartite correlation network
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R Package to Backtest Time Series Models
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mbstsby cran
:exclamation: This is a read-only mirror of the CRAN R package repository. mbsts — Multivariate Bayesian Structural Time Series
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AveragingCorrelationsby SigurdJanson
Functions and analyses to illustrate the performance of correction methods that allow averaging correlation coefficients.
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multibreakby loicym
Implements the multivariate time series break detection of Bai, Lumsdaine and Stock (1998)
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ElectionDataby nunompmoniz
Time Series Data on the 2019 Parliamentary Elections in Portugal
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Dejavuby kdwang1808
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tsForecastRby xavierkamp
R package consisting of functions and tools to facilitate the use of traditional time series and machine learning models to generate forecasts on univariate or multvariate data. Different backtesting scenarios are available to identify the best performing models.
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fgv-time-series-analysisby ldaniel
Practicing Time Series Analysis.
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TukeySensby JiajingZ
R package for sensitivity analysis method in causal inference based on Tukey's Factorization
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Electricity-Loadby skp2
Predict Electricity load from historical time series
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candlePlotterby dominikduda
Prints OHLC time series with style
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pctsby GeoBosh
An R package for modelling periodically correlated and periodically integrated time series
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VaDER_supporting_codeby johanndejong
Supporting code for the manuscript "Deep learning for clustering of multivariate clinical patient trajectories with missing values"
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Grocery_items_time-series_demands_forecastingby sushil1792
#ARIMA #PROPHET #ETS #XGBOOST In this study, I developed and compared the performance of time-series prediction algorithms such as ARIMA, ETS and PROPHET for forecasting demand of Grocery items for a retail store chain in Ecuador
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CPRD_copd_analysisby prockenschaub
This is the R code used to analyse the data for paper "Opportunities to reduce antibiotic prescribing for patients with COPD in primary care"
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stock-price-prediction-in-Time-Seriesby sidoff8
ARIMA modelling
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trendchangeby patakamuri
Trend Analysis Using Innovative Trend Analysis Method and Change Point Analysis Using Seqential Mann-Kendall Plot and Distribution Free Cumulative Sum Plot
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Time-Series-Analysis-and-Forecastingby parthakuila
Build time series modelling and evaluation the best model. Build model like ARIMA, Exponential Smoothing, TBATS, NN and others. Compare the best model forecast the next 30 , 60 data points.
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MultiVariateLSTMWithKerasby RJHKnight
An R port of the Multivariate Time Series Forecasting with Keras blog post
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Hunsinger_StochasticForecastby AppliedDemogToolbox
Eddie's Stochastic Population Forecast Code
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hierTsby gcorani
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YahooTickersby Reckziegel
Download and Model Stock Index Constituents From Yahoo Finance
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forecast_catboostby mk-oh
Time-series modeling with catboost ( R Ver. )
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Building-Breather-Part-3by alexbaramilis
Part 3 of my Building Breather series. https://github.com/alexbaramilis/Building-Breather
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Building-Breather-Part-1by alexbaramilis
Part 1 of my Building Breather series. https://github.com/alexbaramilis/Building-Breather
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Stock_Analysis_Prediction_ARIMA_Modified_Fourier_Series_Rby myrondza
Stock Price Prediction using ARIMA model with Fourier Series
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Structural-Breaksby agustinpalao
Time Series structural break analysis using Bai-Perron method
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CANYON-Bby HCBScienceProducts
Matlab and R routines to robustly estimate open ocean CO2 variables and macronutrients from T, S and O2 data using Bayesian neural networks ("CANYON-B") of Bittig et al. (2018) Front. Mar. Sci. 5:328. http://dx.doi.org/10.3389/fmars.2018.00328
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inSilecoModby inSileco
:package: Package containing functions for ecological model used in disturbance ecology series
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forecastMLby RamiKrispin
Time series forecasting with linear regression and machine learning methods
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nz_ed_access_unbrokeredby lawaFreshwater
Scripts and reference data for accessing GIS and Time series servers
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Sales-time-series-predictionby CG-R8
Time series prediction system in R (RStudio) for given real-time e-commerce dataset of thousands of products, customers, and categories with the help of data mining algorithms (ARIMA, Holt Winter, STL, ETS).
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Evaluation-procedures-for-forecasting-with-spatio-temporal-databy mrfoliveira
"Evaluation procedures for forecasting with spatio-temporal data" -- ECML 2018
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KanyeCausalImpactby benlistyg
Using Bayesian Structural Time Series to empirically test the Kanye Conjecture
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steal-basis-rby gmahjub
R version of the stealBasis financial time series analysis project.
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nautilusby battleVerse
Sensor performance analysis in the battleVerse
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StochasticPQRUTby valeriyafilipova
Model for estimating return periods for flood events
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compenginetsby robjhyndman
Time series data from http://www.comp-engine.org/
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fennecby fennecdb
General purpose timeseries database
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pcsolby EDMANSolar
a set of functions to compute solar irradiance under clear sky conditions
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structural_breakby bootstrap86
Testing for and Detecting Stuctural Breaks in Time Series Data
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chapter_IFmethodsby theresasophia
Code for the chapter "Iterated filtering methods for Markov process epidemic models"
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Motionsby AlexeySAntonov
Based on a series of articles by Nicolas Roard Medium
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aggregationby lynnyi
Methods for aggregating p-values
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R-Package-lprojby ctbrownlees
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modifiedmkby patakamuri
Non-parametric Mann-Kendall trend tests
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QENIEby marcus-seldin
Correlation-based approach for identification of endocrine interactions
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temperatureresponseby low-decarie
R package for fitting a suite equations for the unimodal response to temperature
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tstmle01by podTockom
R/tstmle01: Estimation and Inference for Marginal Causal Effect with Single Binary Time Series
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cbceby miheerdew
Finding communities in a bipartite correlation network
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backtestby joshoberman
R Package to Backtest Time Series Models
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