Read Swiss time series data from the 'KOF Data' API, <https://datenservice.kof.ethz.ch>. The API provides macro economic time series data mostly about Switzerland. The package itself is a set of wrappers around the 'KOF Datenservice' API. The 'kofdata' package is able to consume public information as well as data that requires an API token.

To test if a tensor time series following a Tucker-decomposition factor model has a Kronecker product structure. Supplementary functions for tensor reshape and its reversal are also included.

Maximum likelihood estimation of component lifetime parameters
    from system-level observations of k-out-of-n systems. Supports
    exponential and Weibull component distributions under multiple observation
    schemes: Scheme 0 (system lifetime only), Scheme 1 (periodic inspection),
    and Scheme 2 (complete monitoring). Provides an EM algorithm for Weibull
    parallel systems and Fisher information comparison across schemes. The
    k-out-of-n framework unifies series (k=1) and parallel (k=m) systems as
    a censoring problem on component lifetimes. Conforms to the
    'likelihood.model' generics and returns fitted objects compatible with
    'algebraic.mle'. The data-generating process and topology infrastructure
    (system survival, density, signature, structure function, importance
    measures) are delegated to the 'dist.structure' package; 'kofn' focuses
    exclusively on inference for the k-out-of-n family.

Provides a function that uses a genetic algorithm to search for a subset
 of size k from the integers 1:n, such that a user-supplied objective function 
 is minimized at that subset.  The selection step is done by tournament selection 
 based on ranks, and elitism may be used to retain a portion of the best solutions 
 from one generation to the next. Population objective function values may 
 optionally be evaluated in parallel.

Rank-based tests for enrichment of KOG (euKaryotic Orthologous Groups) classes with up- or down-regulated genes based on a continuous measure. The meta-analysis is based on correlation of KOG delta-ranks across datasets (delta-rank is the difference between mean rank of genes belonging to a KOG class and mean rank of all other genes). With binary measure (1 or 0 to indicate significant and non-significant genes), one-tailed Fisher's exact test for over-representation of each KOG class among significant genes will be performed.