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_pkgdown.yml
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_pkgdown.yml
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url: https://business-science.github.io/timetk/
template:
bootstrap: 5
bootswatch: lux
params:
ganalytics: G-20GDZ5LL77
navbar:
bg: primary
title: timetk
left:
- icon: fa-home
href: index.html
- text: Start
href: articles/TK04_Plotting_Time_Series.html
- text: Articles
href: articles/index.html
menu:
- text: Visualization
- text: Plotting Time Series
href: articles/TK04_Plotting_Time_Series.html
- text: Plotting Seasonality and Correlation
href: articles/TK05_Plotting_Seasonality_and_Correlation.html
- text: '---'
- text: Data Wrangling
- text: Time Series Data Wrangling
href: articles/TK07_Time_Series_Data_Wrangling.html
- text: '---'
- text: Machine Learning
- text: Time Series Machine Learning
href: articles/TK03_Forecasting_Using_Time_Series_Signature.html
- text: Anomaly Detection
href: articles/TK08_Automatic_Anomaly_Detection.html
- text: Clustering
href: articles/TK09_Clustering.html
- text: '---'
- text: Time Series Fundamentals
- text: Calendar Features
href: articles/TK01_Working_With_Time_Series_Index.html
- text: Frequency and Trend
href: articles/TK06_Automatic_Frequency_And_Trend_Selection.html
- text: '---'
- text: Time Sequences & Data Structures
- text: Intelligent Date & Time Sequences
href: articles/TK02_Time_Series_Date_Sequences.html
- text: Time Series Class Conversion (tbl, ts, zoo, & xts)
href: articles/TK00_Time_Series_Coercion.html
- text: API
href: reference/index.html
menu:
- text: API Functions
- icon: fa-home
text: Function Reference
href: reference/index.html
- text: '---'
- text: Change History
- text: News
href: news/index.html
- text: R Ecosystem
menu:
- text: Forecast
- text: Modeltime (Forecasting)
href: https://business-science.github.io/modeltime/
- text: TimeTK (Time Series Analysis)
href: https://business-science.github.io/timetk/
- text: '---'
- text: Improve
- text: Modeltime Ensemble (Blending Forecasts)
href: https://business-science.github.io/modeltime.ensemble/
- text: Modeltime Resample (Backtesting)
href: https://business-science.github.io/modeltime.resample/
- text: '---'
- text: Scale
- text: Modeltime H2O (AutoML)
href: https://business-science.github.io/modeltime.h2o/
- text: Modeltime GluonTS (Deep Learning)
href: https://business-science.github.io/modeltime.gluonts/
- text: Python
menu:
- text: Forecast
- text: Timetk for Python (Time Series Analysis)
href: https://business-science.github.io/pytimetk/
- icon: fas fa-graduation-cap
text: Learn
href: https://university.business-science.io/p/ds4b-203-r-high-performance-time-series-forecasting/
right:
- icon: fa-github
href: https://github.com/business-science/timetk
reference:
- title: Plotting Time Series
desc: __Detect relationships through visualizations__
- subtitle: Time Series Plotting
contents:
- plot_time_series
- plot_time_series_boxplot
- plot_time_series_regression
- subtitle: Correlation, Seasonalilty, & Anomaly Plotting
contents:
- contains("plot_acf")
- contains("plot_anomaly")
- contains("plot_seasonal")
- contains("plot_stl")
- title: Time Series Data Wrangling Operations
desc: __Extension for `dplyr` for time-series data manipulations__
- subtitle: Data Frame Operations
contents:
- contains("summarise")
- contains("mutate")
- pad_by_time
- filter_by_time
- filter_period
- slice_period
- condense_period
- future_frame
- subtitle: Anomaly Detection
contents:
- anomalize
- contains("plot_anomalies")
- subtitle: Function Operations
contents: slidify
- subtitle: Vector Operations
contents:
- between_time
- add_time
- title: Time Series Features
desc: Tidy integration with `tsfeatures`
contents: tk_tsfeatures
- title: Augment Operations (Quickly Add Many Features)
desc: __Add multiple columns to the original data. Respects `dplyr` groups.__
contents:
- tk_augment_timeseries_signature
- tk_augment_holiday_signature
- tk_augment_slidify
- tk_augment_differences
- tk_augment_lags
- starts_with("tk_augment")
- title: Vectorized Transformations
desc: __Use with `mutate` to apply vectorized transformations to time series data__
contents:
- contains("box_cox_vec")
- contains("diff_vec")
- contains("lag_vec")
- standardize_vec
- normalize_vec
- contains("_vec")
- title: Feature Engineering Operations (Recipe Steps)
desc: __Preprocessing & feature engineering operations for use with `recipes` and
the `tidymodels` ecosystem__
- subtitle: Engineered Features
- contents:
- step_timeseries_signature
- step_holiday_signature
- step_fourier
- subtitle: Lags & Diffs
desc: See `recipes::step_lag()` for lagged features.
- contents: step_diff
- subtitle: Smoothing & Rolling
- contents:
- step_smooth
- step_slidify
- step_slidify_augment
- subtitle: Variance Reduction
desc: See `recipes::step_log()` for log transformation.
- contents:
- step_box_cox
- step_log_interval
- subtitle: Add Rows to a Time series
contents: step_ts_pad
- subtitle: Imputation & Outlier Cleaning
desc: See `recipes::step_rollimpute()` for rolling imputation.
- contents:
- step_ts_impute
- step_ts_clean
- title: Cross Validation Operations (Rsample & Tune)
desc: __Resampling for time series cross validation using `rsamples`__
- subtitle: Time Series Cross Validation (Resample Sets)
contents:
- time_series_split
- time_series_cv
- subtitle: Cross Validation Plan Visualization (Resample Sets)
desc: Uses the output of `time_series_cv` or `rsample::rolling_origin`
contents:
- plot_time_series_cv_plan
- tk_time_series_cv_plan
- title: Index Operations
desc: __Extract and check the date or date-time index.__
contents:
- starts_with("tk_index")
- starts_with("has_timetk_idx")
- title: Make Operations
desc: __Make time series sequences.__
contents:
- tk_make_timeseries
- starts_with("tk_make_future")
- starts_with("tk_make")
- title: Get Operations
desc: __Get summaries, frequency, and signatures from the time series index.__
contents:
- tk_get_timeseries_signature
- tk_get_holiday_signature
- contains("tk_get")
- title: Diagnostic Operations
desc: __These power the time series plotting functions__
contents:
- tk_summary_diagnostics
- tk_anomaly_diagnostics
- tk_acf_diagnostics
- tk_seasonal_diagnostics
- tk_stl_diagnostics
- title: Conversion Operations
desc: __Functions for converting between common time series formats.__
contents:
- tk_tbl
- tk_ts
- tk_ts_
- tk_xts
- tk_xts_
- tk_zoo
- tk_zoo_
- tk_zooreg
- tk_zooreg_
- title: Time Scale Template
desc: __The timescale template is used to automate frequency and trendcycle calculations.__
contents: contains("time_scale")
- title: Time Series Datasets
desc: __Time series from various forecasting competitions. Domains include economic,
retail, and web (google analytics)__
contents:
- m4_hourly
- m4_daily
- m4_weekly
- contains("m4_")
- contains("walmart")
- contains("wikipedia")
- bike_sharing_daily
- taylor_30_min
- FANG
- title: Date Utilities
contents:
- parse_date2
- is_date_class
- title: Package Information
contents:
- timetk