imputeFin
0.1.2Imputation of Financial Time Series with Missing Values and/or Outliers
Overview
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. doi:10.1109/TSP.2019.2899816.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-07-2011 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-07-1911 OK · 1 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 86%
- Documented parameters
- 98%
- Return-value docs
- 88%
- References docs
- 50%
Downloads
Repository
Repository practices
4 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/dppalomar/imputefin on 2026-07-19.
Dependencies
Nothing depends on this yet.
Code & Tests
- Cyclomatic complexity
- 3.0 median / 39 max
- Test cases
- 27 / 0.21 per code line
Test coverage
Line coverage
76%
Expression
78.5%
Tests / Examples
76.0% / 41% ex
Functions
42 8 exported
Complexity
7.5 avg / 39 max
Call network
42 nodes / 61 edges
Call graph
Open call graph →Lowest coverage
42 functions| Function | Cyclo | Coverage |
|---|---|---|
| impute_OHLC exp | 1 | 0% |
| impute_rolling_AR1_Gaussian exp | 4 | 0% |
| plot_imputed exp | 13 | 0% |
| fit_AR1_Gaussian_complete | 9 | 0% |
| fit_AR1_t_complete | 16 | 0% |
| loglikFullObs | 1 | 0% |
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 0.1.2Latest
- 0.1.12020-07-11 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 0.1.02019-12-13
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2019-12-13
- Total releases
- 3 / 7 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 13 KB / 3 files
- Download size
- 1.0 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet