Changes in version 0.1.7 (2023-08-09)                  

  - Replacing deprecated functions:
      - ts_split - replacing the is.tsibble function with is_tsibble
        function
      - ts_grid - replacing the future package lapply function with the
        parallel package implementation

                 Changes in version 0.1.6 (2020-01-21)                  

  - Fixing errors on the train_model function:
      - Error with the forecast output
      - Error with the nnetar model
  - Replacing the xts::indexClass function with xts::tclass function
  - Removing the ts_backtesting function, which was replaced by the
    train_model function
  - Removing the ts_acf and ts_pacf functions, the ts_cor will replace
    them
  - Removing the bsts package from the package dependency

                 Changes in version 0.1.5 (2019-10-28)                  

Package license

Changing the package license from GPL-3 to MIT

New functions

  - train_model - a flexible framework for training, testing,
    evaluating, and forecasting models. This function provides the
    ability to run multiple models with backtesting or single
    training/testing partitions
  - plot_model - animation the performance of the train_model output on
    the backtesting partitions
  - plot_error - plotting the error distribution of the train_model
    output
  - ts_cor - for acf and pacf plots with seasonal lags
  - arima_diag - a diagnostic plot for identify the AR, MA and
    differencing components of the ARIMA model

Deprecated functions

  - ts_backtesting - will be replaced by the train_model function
  - ts_acf / ts_pacf functions - will be replaced by the ts_cor function

Fix errors

  - ts_seasonal - aligning the box plot color
  - ts_plot - setting the dash and marker mode for multiple time series

                 Changes in version 0.1.4 (2019-04-13)                  

New functions

  - forecast_sim - creating different forecast paths for forecast
    objects (when applicable), by utilizing the underline model
    distribution with the simulate function
  - ts_grid - tuning time series models with grid search approach using
    backtesting method. Currently, support only the Holt-Winters model
  - plot_grid - plotting the output of the ts_grid function

Fix errors

  - ts_plot, test_forecast - avoid default setting of the plot_ly
    function, and set explicitly the plot setting (e.g., color, line
    mode, etc.). This allows using the function with the plotly subplot
    function
  - ts_seasonal - define the order of the frequency units of the box
    plot option plot_forecast - fixing a gap between the forecast values
    and the time (x-axis) values

                 Changes in version 0.1.3 (2018-11-25)                  

  - ts_to_prophet function for converting ts objects ("ts", "zoo" and
    "xts" class) to prophet object
  - ccf_plot function for plotting corss correlation lags between two
    time series
  - Fixed error in the ts_backtesting function - supprting xreg option

                 Changes in version 0.1.2 (2018-09-21)                  

New functions

  - ts_backtesting - a horce race of multiple forecasting models with
    backtesting
  - ts_quantile - time series quantile plot for time series data
  - ts_seasonal - supports multiple inputs and new color palattes

                 Changes in version 0.1.1 (2018-02-07)                  

New functions

  - New options for the seasonality plot
  - Heatmap and surface plots
  - Polar plot
  - Converting function from xts and zoo to ts class
  - Spliting function for ts object for training and testing partitions
  - Time series lags plot - ts_lags() function
  - Function ts_split() to split 'ts' object into training and testing
    partitions
  - Functions for converting xts and zoo objects for ts object:
      - xts_to_ts(), and
      - zoo_to_ts()
  - Two types for the seasonal_ly() plot:
      - "normal" - seasonal variation by year, or
      - "cycle" - seasonal variation by the cycle units over time
        (months or quarters)
      - "polar" - polar plot for seasonality
      - "box" - box-plot by cycle units
  - Decompose plot with the decompose_ly() function
  - Data set - US monthly total vehicle sales: 1976 - 2017 (USVSales),
    'ts' object
  - Data set - US monthly civilian unemployment rate: 1948 - 2017
    (USUnRate), 'ts' object
  - Data set - US monthly natural gas consumption: 2000 - 2017 (USgas),
    'ts' object
  - Data set - University of Michigan Consumer Survey, Index of Consumer
    Sentiment: 1980 - 2017 (Michigan_CS), 'xts' object
  - Data set - Monthly crude Oil Prices: Brent - Europe: 1987 - 2017
    (EURO_Brent), 'zoo' object

                 Changes in version 0.1.0 (2018-01-03)                  

  - Function for plotting univariate and multivariate time series data
  - Evaluation plot for the testing set (hold-out data)
  - Interactive seasonality plot
  - Functions for interactive plot for the ACF and PACF