Calculates total survey error (TSE) for one or more surveys, using common scale-dependent and/or scale-independent metrics.  On TSE, see: Weisberg, Herbert (2005, ISBN:0-226-89128-3); Biemer, Paul (2010) <doi:10.1093/poq/nfq058>.

The library allows to perform a multivariate time series
    classification based on the use of Discrete Wavelet Transform for
    feature extraction, a step wise discriminant to select the most
    relevant features and finally, the use of a linear or quadratic
    discriminant for classification. Note that all these steps can be done
    separately which allows to implement new steps.  Velasco, I., Sipols,
    A., de Blas, C. S., Pastor, L., & Bayona, S. (2023)
    <doi:10.1186/S12938-023-01079-X>.  Percival, D. B., & Walden, A. T.
    (2000,ISBN:0521640687).  Maharaj, E. A., & Alonso, A. M. (2014)
    <doi:10.1016/j.csda.2013.09.006>.

Autoregressive distributed lag (A[R]DL) models (and their reparameterized equivalent, the Generalized Error-Correction Model [GECM]) (see De Boef and Keele 2008 <doi:10.1111/j.1540-5907.2007.00307.x>) are the workhorse models in uncovering dynamic inferences. ADL models are simple to estimate; this is what makes them attractive. Once these models are estimated, what is less clear is how to uncover a rich set of dynamic inferences from these models. We provide tools for recovering those inferences in three forms: causal inferences from ADL models, traditional time series quantities of interest (short- and long-run effects), and dynamic conditional relationships.

Calculates total survey error (TSE) for one or more surveys, using both scale-dependent and scale-independent metrics.  Package works directly from the data set, with no hand calculations required: just upload a properly structured data set (see TESTIND and its documentation), properly input column names (see functions documentation), and run your functions.  For more on TSE, see: Weisberg, Herbert (2005, ISBN:0-226-89128-3); Biemer, Paul (2010) <doi:10.1093/poq/nfq058>; Biemer, Paul et.al. (2017, ISBN:9781119041672); etc.