Improved Rd Cross-References: Fixed \link{} targets in documentation by adding explicit package anchors (e.g., \link[fda]{fd}), in compliance with updated CRAN HTML reference manual policies.
ð ï¸ Build Compatibility: Ensured compatibility with current R build toolchains by verifying successful compilation on Windows using Rtools.
The new following functions are replaced to GitHub load data:
loadCallcenterData()loadJambiData()loadMontanaData()loadAustinData()loadUtqiagvikData()In these updated functions, upon downloading the data files from GitHub into a temporary directory (not the global environment), the target objects are now returned within the function. This modification allows users to save the data into an arbitrary variable of their choice.
Rfssa 3.0.2 Minor improvements and bug fixes3Dline and 3DSurface type plots in plotly_funts that prevented plotting.The name fts has been modified to funts to avoid any clashes with the package. Furthermore, the class of funts has bee transitioned from S4 to S3 to ensure better compatibility and consistency within the package. These changes are aimed at preventing any conflicts when using Rfssa in conjunction with other packages like rainbow, enhancing the user experience.
All the methods for funts have re-implemented and introduced new generic methods such as length(), print(), and plot() to provide a more comprehensive and user-friendly interface.
The plot() method for funts class objects (formerly fts) has been renamed to plotly_funts(). This new name more accurately reflects the type of plots it generates, which are based on plotly graphics.
An S3 class named fforecast is added to encapsulate the output of the fforecast() function. This class is designed to provide a more organized and intuitive structure for handling forecasted functional time series (FTS) data.
Three convenient functions, namely loadJambiData(), loadCallcenterData(), and loadMontanaData() are added. These functions have been designed to simplify the process of acquiring the raw dataset from the web and loading it into the global environment.
funts function to capture the duration of the time series. These parameters provide flexibility for users to specify time information in a more structured and standardized manner. Users can now set start and end using various time and date classes such as Date, POSIXct, or POSIXt, allowing for better representation of time.fts updated to be a constructor of a new S4 object that is used to create objects of class fts. Note that the user may specify their own basis and grid or may specify that they want the constructor to build such attributes automatically. In addition, the fts may be comprised of variables observed over one or two-dimensional domains. This constructor also has custom validity checks built in to help the user construct fts objects.
fts.plot was updated to allow for plotting of fts variables observed over two-dimensional domains.
fssa updated so that univariate and multivariate fts objects may be decomposed where each variable may be observed over a one or two-dimensional domain. In addition, the speed of the decomposition process was increased by using the Rspectra and RcppEigen R packages, and the Eigen C++ package.
plot.fssa was updated to allow the user to plot the left singular functions for fts whose variables have domains over two-dimensions. All other plotting options were updated to handle the two-dimensional domain functionality as well.
freconstruct updated to allow for the reconstruction stage of univariate and multivariate fts objects whose variables might be might observed over one or two-dimensional domains.
Arithmetic operations such as fts addition and fts subtraction have been updated to allow for numeric vector-fts arithmetic.
fforecast was added to allow for nonparametric forecasting of fts objects via fssa recurrent or fssa vector forecasting. The approach begins with objects of class fssa. The fts may be univariate or multivariate however, the variables must be observed over a one-dimensional domain. Different dimensional domains forecasting is under development.
Montana was added to provide an example of a multivariate fts whose variables are observed over a one-dimensional and two-dimensional domain.
load_github_data was added to allow the user to load the Callcenter, Jambi, and Montana datasets from GitHub which significantly reduced the size of the package. In addition, this same function may be used to load data from any other public GitHub repository.
line type plots in plot.fts that prevented plotting.RetroSearch is an open source project built by @garambo | Open a GitHub Issue
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