'Rcpp' implementation of the multivariate Kim filter, which combines the Kalman and Hamilton filters for state probability inference. 
  The filter is designed for state space models and can handle missing values and exogenous data in the observation and state equations.
  Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.

A collection of useful functions not found anywhere else,
        mainly for programming: Pretty intervals, generalized lagged
        differences, checking containment in an interval, and an
        alternative interface to assign().

Analysis of kin-cohort studies. kin.cohort provides estimates of age-specific 
 cumulative risk of a disease for carriers and noncarriers of a mutation. The cohorts are
 retrospectively built from relatives of probands for whom the genotype is known. Currently 
 the method of moments and marginal maximum likelihood are implemented. Confidence intervals 
 are calculated from bootstrap samples.
 Most of the code is a translation from previous 'MATLAB' code by N. Chatterjee.

Functions for simulating and estimating kinship-related dispersal. Based
    on the methods described in M. Jasper, T.L. Schmidt., N.W. Ahmad, S.P. Sinkins & A.A. 
    Hoffmann (2019) <doi:10.1111/1755-0998.13043> "A genomic approach to inferring kinship 
    reveals limited intergenerational dispersal in the yellow fever mosquito".
    Assumes an additive variance model of dispersal in two dimensions, compatible with 
    Wright's neighbourhood area. Simple and composite dispersal simulations are supplied, 
    as well as the functions needed to estimate parent-offspring dispersal for simulated or 
    empirical data, and to undertake sampling design for future field studies of dispersal. 
    For ease of use an integrated Shiny app is also included.

Allows analyzing time series representing two-dimensional movements.
    It accepts a data frame with a time (t), horizontal (x) and vertical (y) coordinate as columns,
    and returns several dynamical properties such as speed, acceleration or curvature.