From Visual Analytics and Applications
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| | === Forecasting === | | === Forecasting === |
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| − | == Packages ==
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| − | {|class="wikitable"
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| − | ! Package Name !! Descriptions
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| − | | ''RShiny'' || Interactive web applications for data visualization
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| − | | ''Tidyverse: tidyr, dplyr, ggplot2'' || Tidying and manipulating data for visualizing in ggplot2
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| − | | ''Shinythemes'' || Provide consistent UI elements for aesthetics
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| − | | ''forecast, broom, sweep'' || Packages used to "tidy" data models for easy forecasting. Forecast package uses ''ts'' objects that is difficult to manipulate. sw_sweep from the sweep package uses broom-style tidiers to extract model infomation into 'tidy' data frames. sweep package also uses timekit at the back-end to maintain the original time series index throughout the whole process.
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| − | | ''tibbletime'' || Time-based data subsetting
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| − | | ''lubridate'' || Easy manipulation of datetime data
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| − | | ''timetk'' || Extracting/checking of datetime index from ts objects
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| − | |}
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Revision as of 02:48, 1 December 2017
Background
Time Series Analysis
Case Application
Problem and Motivation
Data Preparation
Application and Analysis
Basic Time Series
Clustering
Forecasting
