Package: conduits 1.0.0

Puwasala Gamakumara

conduits: CONDitional UI for Time Series normalisation

Provide a user interface for conditionally normalising a timeseries.

Authors:Puwasala Gamakumara [aut, cre], Priyanga Dilini Talagala [aut], Rob J. Hyndman [aut]

# Install 'conduits' in R:

install.packages('conduits', repos = c('https://robjhyndman.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

NEON_PRIN_5min_cleaned - Anomaly removed data for water quality variables aggregated at 5-minute intervals from Pringle Creek, Texas.

On CRAN:

Last updated 2 years agofrom:80a48697c0. Checks:OK: 3 NOTE: 4. Indexed: no.

Help page	Topics
Augment data with information from a conditional auto-correlation fit	augment.conditional_acf
Augment data with information from a conditional cross-correlation fit	augment.conditional_ccf
Augment data with information from a conditional mean fit or conditional variance fit	augment.conditional_moment
Computing bootstrapped confidence intervals for dt	calc_dt_CI
Computing conditional autocorrelations at given lags	conditional_acf
Computing conditional cross-correlations at given lags	conditional_ccf
Estimating conditional mean of a time series	conditional_mean
Estimating conditional variance of a time series	conditional_var
conduits: CONDitional User Interface for Time Series normalisation	conduits
Estimating time delay between two sensors in a river system	estimate_dt
Anomaly removed data for water quality variables aggregated at 5-minute intervals from Pringle Creek, Texas.	NEON_PRIN_5min_cleaned
Normalize a series using conditional moments	normalize
Unnormalize a series using conditional moments	unnormalize