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fpcb

Functional predictive confidence bands

https://github.com/nicolashernandezb/fpcb

Science Score: 10.0%

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    Low similarity (7.9%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Functional predictive confidence bands

Basic Info
  • Host: GitHub
  • Owner: nicolashernandezb
  • License: gpl-3.0
  • Language: R
  • Default Branch: main
  • Size: 85 KB
Statistics
  • Stars: 0
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 5 years ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

fpcb -- Functional Predictive Confidence Bands

R-CMD-check <!-- badges: end -->

fpcb provides estimation and prediction functions for autoregressive Hilbert processes of order one within the framework of reproducing kernel Hilbert spaces.

Installation

You can install the released version of fpcb from CRAN with :

r install.packages("fpcb")

Or install the development version from GitHub with: ``` r

install.packages("remotes")

remotes::install_github("nicolashernandezb/fpcb") ```

Example

This is a basic example which shows you how to solve a common problem:

``` r library(fpcb) require(ftsa) t <- seq(0, 1,length.out = nrow(ftsa::pm10GR$y)) kernel <- fpcb::rk(grid = t, r=10, sigma = 0.01) data <- t(sqrt(ftsa::pm10GR$y)) fd.curves <- fpcb::fdatarkhs(curves = data, rk = kernel) model <- fpcb::arhrkhs(fd.curves)

POINT PREDICTION

predict.rkhs <- fpcb::predict_rkhs(model, bands=F) matplot(t,t(data), xlab='time', ylab='PM10 dataset', col='gray', lty=1, type='l') matlines(t,t(fd.curves$fdata), col='blue', lty=1) lines(t,predict.rkhs$forecast,col='red',lty=1,lwd=1.5) legend("topright",lty=1, col=c('gray','blue','red'), legend=c('PM10 curves','PM10 smoothed curves','Point Forecast (n+1)'))

PREDICTIVE BANDS

predict.rkhs <- fpcb::predict_rkhs(model, bands=T, B = 1000, level = 0.95) matplot(t,t(data), xlab='time', ylab='PM10 dataset', col='gray', lty=1, type='l') lines(t,predict.rkhs$forecast,col='red',lty=1,lwd=1.5) lines(t,predict.rkhs$UB,col='blue',lty=2,lwd=1.5) lines(t,predict.rkhs$LB,col='blue',lty=2,lwd=1.5) legend("topright",lty=c(1,1,2), col=c('gray','red','blue'), legend=c('PM10 curves','Point Forecast (n+1)','95% Conf. Band')) ```

Owner

  • Login: nicolashernandezb
  • Kind: user
  • Location: London, UK
  • Company: University College London

GitHub Events

Total
  • Push event: 3
Last Year
  • Push event: 3

Committers

Last synced: over 3 years ago

All Time
  • Total Commits: 68
  • Total Committers: 3
  • Avg Commits per committer: 22.667
  • Development Distribution Score (DDS): 0.118
Top Committers
Name Email Commits
nicolashernandezb 3****b@u****m 60
cugliari J****i@u****r 6
Jairo Cugliari j****i@g****m 2
Committer Domains (Top 20 + Academic)
univ-lyon2.fr: 1

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Packages

  • Total packages: 1
  • Total downloads:
    • cran 199 last-month
  • Total docker downloads: 21,613
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
cran.r-project.org: fpcb

Predictive Confidence Bands for Functional Time Series Forecasting

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 199 Last month
  • Docker Downloads: 21,613
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Average: 39.2%
Downloads: 66.6%
Maintainers (1)
nicolashernandezb@gmail.com
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • FNN * imports
  • ftsa * imports