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PRISM.forecast  

Penalized Regression with Inferred Seasonality Module - Forecasting Unemployment Initial Claims using 'Google Trends' Data
View on CRAN: Click here


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

Install from Github:
library("remotes")
install_github("cran/PRISM.forecast")

Install by package version:
library("remotes")
install_version("PRISM.forecast", "0.2.1")



Attach the package and use:
library("PRISM.forecast")
Maintained by
Dingdong Yi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-07-01
Latest Update: 2020-10-21
Description:
Implements Penalized Regression with Inferred Seasonality Module (PRISM) to generate forecast estimation of weekly unemployment initial claims using 'Google Trends' data. It includes required data and tools for backtesting the performance in 2007-2020.
How to cite:
Dingdong Yi (2018). PRISM.forecast: Penalized Regression with Inferred Seasonality Module - Forecasting Unemployment Initial Claims using 'Google Trends' Data. R package version 0.2.1, https://cran.r-project.org/web/packages/PRISM.forecast. Accessed 04 Jun. 2026.
Previous versions and publish date:
0.1.6 (2018-07-01 15:31), 0.2.0 (2020-04-22 12:02)
Other packages that cited PRISM.forecast R package
View PRISM.forecast citation profile
Other R packages that PRISM.forecast depends, imports, suggests or enhances
Complete documentation for PRISM.forecast
Functions, R codes and Examples using the PRISM.forecast R package
Some associated functions: back_test . evaluation_table . load_5y_search_data . load_claim_data . prism . prism_batch . var_generator . 
Some associated R codes: back_test.R . evaluation_table.R . load_5y_search_data.R . load_claim_data.R . prism.R . prism_batch.R . var_generator.R .  Full PRISM.forecast package functions and examples
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