MLE for H parameter in FGN; MLE for regression with FGN error; simulation of FGN

MLE for H parameter in FGN; MLE for regression with FGN
error; simulation of FGN

Fractional Gaussian Noise, estimation and simulaton
MLE for H parameter in FGN; MLE for regression with FGN
error; simulation of FGN; print, summary, plot, coef,
residuals, Boot methods.

Fractional Gaussian Noise (FGN) and simple models for hyperbolic
decay time series
Efficient exact MLE and Whittle MLE estimation of four
simple long memory time series models.

Fractional Gaussian Noise and hyperbolic decay time series model
fitting
Exact MLE and Whittle MLE estimation for various
hyperbolic decay time series models.

Fractional Gaussian Noise and power law decay time series model
fitting
Exact MLE and Whittle MLE estimation for power law decay models.

Feature Grouping and Selection Over an Undirected Graph
Implement algorithms for feature grouping and selection over an undirected graph, solves problems like graph fused lasso, graph OSCAR and so on.
The header file blaswrap.h, f2c.h and fgsg.h are from the
VisualStudio library created by Julie Langou.

Feature grouping and selection over an undirected graph
FGSG package implements algorithms for feature grouping and selection over an undirected graph.

This is a package for implementation of Flury-Gautschi
algorithms.

Fractional Hot Deck and Fully Efficient Fractional Imputation
c(person("Jongho","Im", role="aut",email="jonghoim@iastate.edu"),
person("Inho","Cho", role=c("aut","cre"), email="icho@iastate.edu"),
person("Jaekwang","Kim", role="aut", email="jkim@iastate.edu"))
Jongho Im [aut], Inho Cho [aut, cre], Jaekwang Kim [aut]
Impute general multivariate missing data with the fractional hot deck imputation.

Impute general multivariate missing data with the fractional hot deck imputation of Jaekwang Kim (2011) <doi:10.1093/biomet/asq073>.

Jongho Im [aut],
Inho Cho [aut, cre],
Jaekwang Kim [aut]
Impute general multivariate missing data with the fractional hot deck imputation based on Jaekwang Kim (2011) <doi:10.1093/biomet/asq073>.