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midasr 0.9 (2025-04-07)

Add 5 new models. LSTR-MIDAS and MMM-MIDAS are fitted with midas_nlpr. SI-MIDAS and PL-MIDAS are fitted with midas_sp. Quantile MIDAS model are fitted with midas_qr.
Add new midas lag implementation mlsd. It allows using time series attributes of the data and can align high frequency into low frequency when the number of high frequency periods is not the same for all low frequency periods.
Add support for texreg package. Fitted midasr models can be outputed to nice tables

Remove unexported code
Remove confusing functions dedicated for working with various parameters of MIDAS regression. All of the parameters can now be accessed with coef method. By default coef returns the parameters of NLS problem. With option midas=TRUE, coef returns the MIDAS weights.
Add function plot_midas_coef for graphical inspection of MIDAS weights.
Refactor simulation code, so it is more like arima.sim.
Make forecast return the object of class forecast. Add an option of calculating prediction intervals for forecasts. Currently they are computed via simple bootstraping. This allows using print, summary and plot methods from package forecast.
Move to more consistent naming convention a la Hadley Wickham, this means that dot (.) is only used for S3 method dispatch. If there is no S3 dispatch, the underscore (_) is used. This changes a lot of functions, such as hAhr.test -> hAh_test, all the gradient functions, so revisit your code for possible breakages.
Add ability to pass user defined weight gradients. See the documentation for weight_gradients option for midas_r function.

Add experimental support for nonparametric MIDAS, see Breitung et al. http://www.ect.uni-bonn.de/mitarbeiter/joerg-breitung/npmidas
Add dependency and support to the package optimx. This gives more flexibility in chosing the optimisation method.
Add data sets needed for midasr user guide.
Add GPL-2 licencing
Add function midas_r_simple for fitting MIDAS regressions without formula interface. It can be considerably faster than midas_r.

Fix a bug, where the midas_r_ic_table would not work with formula containing only one term
More explicit error messages are displayed when optimisation fails or when robust covariance matrix cannot be calculated
Add progress indicator to average_forecast function
Fix a bug in data_to_list function, make forecast.midas_r work with midas_u objects.
Fix a bug in average_forecast, rolling samples were turning to recursive ones, thanks to Michael Swan for pointing it out.

Milestone release. Full-fledged support for fitting MIDAS regressions without lagged dependent variable.
Robust and non-robust tests for MIDAS restriction.
The fitted model object has methods for generic functions 'coef', 'deviance', 'fitted', 'residuals', 'predict', 'print', 'residuals', 'summary' and 'vcov'. Additionally it has method 'logLik' for use with 'AIC' and 'BIC' and methods 'estfun' and 'bread' for use with 'vcovHAC' from package sandwich, i.e. there is support for computing robust standard errors for the coefficients
Three demos illustrating the use of the package. They reproduce the results from the article "The statistical content and empirical testing of the MIDAS restrictions".

Initial release. Very basic functionality. Currently only one predictor variable is allowed. Full functionality of the package is reflected in help page of function hAh.test.