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MazamaTimeSeries
View on CRAN: Click
here
Download and install MazamaTimeSeries package within the R console
Install from CRAN:
install.packages("MazamaTimeSeries")
Install from Github:
library("remotes")
install_github("cran/MazamaTimeSeries") Install by package version:
library("remotes")
install_version("MazamaTimeSeries", "0.3.1") Attach the package and use:
library("MazamaTimeSeries")
Maintained by
Jonathan Callahan
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-02-16
Latest Update: 2025-05-17
Description:
Utility functions for working with environmental time series data from known
locations. The compact data model is structured as a list with two dataframes. A
'meta' dataframe contains spatial and measuring device metadata associated with
deployments at known locations. A 'data' dataframe contains a 'datetime' column
followed by columns of measurements associated with each "device-deployment".
Ephemerides calculations are based on code originally found in NOAA's
"Solar Calculator" .
How to cite:
Jonathan Callahan (2022). MazamaTimeSeries: Core Functionality for Environmental Time Series. R package version 0.3.1, https://cran.r-project.org/web/packages/MazamaTimeSeries. Accessed 22 Sep. 2026.
Previous versions and publish date:
0.2.2 (2022-02-16 21:10), 0.2.5 (2022-04-05 20:52), 0.2.7 (2022-08-25 19:22), 0.2.8 (2022-10-13 20:42), 0.2.10 (2023-01-31 01:10), 0.2.12 (2023-05-08 19:40), 0.2.13 (2023-07-12 20:30), 0.2.14 (2023-09-08 07:10), 0.2.15 (2023-09-22 09:20), 0.2.16 (2024-01-22 22:32), 0.3.0 (2024-03-09 00:50), (2026-07-09 08:10)
Other packages that cited MazamaTimeSeries R package
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Other R packages that MazamaTimeSeries depends,
imports, suggests or enhances
Complete documentation for MazamaTimeSeries
Functions, R codes and Examples using
the MazamaTimeSeries R package
Some associated functions: Camp_Fire . Carmel_Valley . MazamaTimeSeries . dot-flagOutliers . dot-sample . example_mts . example_raws . example_sts . mts_check . mts_collapse . mts_combine . mts_distinct . mts_extractDataFrame . mts_filterData . mts_filterDate . mts_filterDatetime . mts_filterMeta . mts_getDistance . mts_isEmpty . mts_isValid . mts_sample . mts_select . mts_selectWhere . mts_summarize . mts_trim . mts_trimDate . pipe . requiredMetaNames . sts_check . sts_combine . sts_distinct . sts_extractDataFrame . sts_filter . sts_filterDate . sts_filterDatetime . sts_isEmpty . sts_isValid . sts_summarize . sts_trimDate . timeInfo .
Some associated R codes: MazamaTimeSeries.R . data.R . mts_collapse.R . mts_combine.R . mts_filterData.R . mts_filterDate.R . mts_filterDatetime.R . mts_filterMeta.R . mts_getDistance.R . mts_sample.R . mts_select.R . mts_selectWhere.R . mts_summarize.R . mts_trim.R . mts_trimDate.R . sts_combine.R . sts_filter.R . sts_filterDate.R . sts_filterDatetime.R . sts_summarize.R . sts_trimDate.R . timeInfo.R . utils-internal.R . utils-mts.R . utils-pipe.R . utils-sampling.R . utils-sts.R . utils-timeInfo.R . Full MazamaTimeSeries package functions and examples
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