Penalized Regression with Inferred Seasonality Module -
Forecasting Unemployment Initial Claims using 'Google Trends'
Data
c(
person("Dingdong", "Yi", email = "ddyi@fas.harvard.edu", role = c("aut", "cre")),
person("Samuel", "Kou", email = "kou@stat.harvard.edu", role = c("aut")))
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 2007-2016.
Dingdong Yi [aut, cre],
Samuel Kou [aut]

c(
person("Dingdong", "Yi", email = "ryan.ddyi@gmail.com", role = c("aut", "cre")),
person("Samuel", "Kou", email = "kou@stat.harvard.edu", role = c("aut")),
person("Shaoyang", "Ning", email = "sn9@williams.edu", role = c("aut")))
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.
Dingdong Yi [aut, cre],
Samuel Kou [aut],
Shaoyang Ning [aut]

Protocol Inspection and State Machine Analysis
The PRISMA package is capable of loading and processing
huge text corpora processed with the sally toolbox
(http://www.mlsec.org/sally/). sally acts as a ver fast
preprocessor which splits the text files into tokens or
n-grams. These output files can then be read with the PRISMA
package which applies testing-based token selection and has
some duplicat-aware, highly tuned Non-Negative Matrix
Factorzation and Principal component Analysis implementation
which allows the processing of very big data sets even on
desktop machines.

The PRISMA package is capable of loading and processing
huge text corpora processed with the sally toolbox
(http://www.mlsec.org/sally/). sally acts as a very fast
preprocessor which splits the text files into tokens or
n-grams. These output files can then be read with the PRISMA
package which applies testing-based token selection and has
some replicate-aware, highly tuned non-negative matrix
factorization and principal component analysis implementation
which allows the processing of very big data sets even on
desktop machines.