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imputeFin
View on CRAN: Click
here
Download and install imputeFin package within the R console
Install from CRAN:
install.packages("imputeFin")
Install from Github:
library("remotes")
install_github("cran/imputeFin")
Install by package version:
library("remotes")
install_version("imputeFin", "0.1.2")
Attach the package and use:
library("imputeFin")
Maintained by
Daniel P. Palomar
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.imputeFin . https://github.com/dppalomar/imputeFin/issues . https://CRAN.R-project.org/package=imputeFin . https://github.com/dppalomar/imputeFin . imputeFin citation info . imputeFin results . imputeFin.pdf . imputeFin_0.1.2.tar.gz . imputeFin_0.1.2.zip . imputeFin_0.1.2.zip . imputeFin_0.1.2.zip . imputeFin_0.1.2.tgz . imputeFin_0.1.2.tgz . imputeFin_0.1.2.tgz . imputeFin_0.1.2.tgz . imputeFin_0.1.2.tgz . imputeFin_0.1.2.tgz . imputeFin archive . https://CRAN.R-project.org/package=imputeFin .
First Published: 2019-12-13
Latest Update: 2021-02-20
Description:
Missing values often occur in financial data due to a variety
of reasons (errors in the collection process or in the processing stage,
lack of asset liquidity, lack of reporting of funds, etc.). However,
most data analysis methods expect complete data and cannot be employed
with missing values. One convenient way to deal with this issue without
having to redesign the data analysis method is to impute the missing
values. This package provides an efficient way to impute the missing
values based on modeling the time series with a random walk or an
autoregressive (AR) model, convenient to model log-prices and log-volumes
in financial data. In the current version, the imputation is
univariate-based (so no asset correlation is used). In addition,
outliers can be detected and removed.
The package is based on the paper:
J. Liu, S. Kumar, and D. P. Palomar (2019). Parameter Estimation of
Heavy-Tailed AR Model With Missing Data Via Stochastic EM. IEEE Trans. on
Signal Processing, vol. 67, no. 8, pp. 2159-2172. .
How to cite:
Daniel P. Palomar (2019). imputeFin: Imputation of Financial Time Series with Missing Values and/or Outliers. R package version 0.1.2, https://cran.r-project.org/web/packages/imputeFin. Accessed 03 Apr. 2025.
Other packages that cited imputeFin R package
View imputeFin citation profile
Other R packages that imputeFin depends,
imports, suggests or enhances
Complete documentation for imputeFin
Functions, R codes and Examples using
the imputeFin R package
Some associated functions: fit_AR1_Gaussian . fit_AR1_t . fit_VAR_t . imputeFin-package . impute_AR1_Gaussian . impute_AR1_t . impute_OHLC . impute_rolling_AR1_Gaussian . plot_imputed . ts_AR1_Gaussian . ts_AR1_t . ts_VAR_t .
Some associated R codes: OHLC.R . estimate_impute_AR1_Gaussian.R . estimate_impute_AR1_t.R . fit_VAR_t.R . imputeFin-package.R . misc.R . outliers.R . plot_imputed.R . ts_AR1_Gaussian.R . ts_AR1_t.R . ts_VAR_t.R . Full imputeFin package functions and examples
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