R (>= 2.0.0), ConvergenceConcepts, dynlm, survival, splines,
nlme, lattice, plm, zoo

boot, car, ConvergenceConcepts, geepack, lmtest, strucchange,
tcltk

boot, car, ConvergenceConcepts, geepack, lmtest, strucchange,
tcltk, plm, zoo

boot, car, ConvergenceConcepts, geepack, lmtest, strucchange,
plm, zoo

Maximum entropy density based dependent data bootstrap.
An algorithm is provided to create a population of time series (ensemble)
without assuming stationarity. The reference paper (Vinod, H.D., 2004) explains
how the algorithm satisfies the ergodic theorem and the central limit theorem.

Hrishikesh D. Vinod <Vinod@fordham.edu>, Javier
López-de-Lacalle <javlacalle@yahoo.es>, and Fred Viole

R (>= 3.5.0), dynlm, nlme, tdigest, hdrcde
Maximum entropy density based dependent data bootstrap.
An algorithm is provided to create a population of time series (ensemble)
without assuming stationarity. The reference paper (Vinod, H.D., 2004 <DOI: 10.1016/j.jempfin.2003.06.002>) explains
how the algorithm satisfies the ergodic theorem and the central limit theorem.

R (>= 3.0.0), dynlm, nlme, tdigest, hdrcde

Univariate and multivariate ECDFs. Currently this produces
step functions (which is what one would expect). Methods for
producing smooth(ish) distribution functions are being
considered. Note, this package is still experimental.

Univariate and multivariate ECDFs. This produces step
functions, methods for producing smooth(ish) distribution
functions are being considered.

Univariate and multivariate empirical cumulative
distribution functions (ECDFs), including both step functions
(true ECDFs) and continuous functions (via interpolation). Plus
special purpose functions for plotting univariate and bivariate
ECDFs.

Univariate and multivariate empirical cumulative
distribution functions (ECDFs), including both step
distribution functions (true ECDFs) and continuous distribution
functions (via interpolation).

Multivariate Empirical Cumulative Distribution Functions
Univariate and multivariate empirical cumulative
distribution functions (ECDFs), including both step
distribution functions (true ECDFs) and continuous distribution
functions.