BeSS (version 2.0.2)

summary.bess: summary method for a "bess.one" object

Description

Print a summary of the "bess.one" object.

Usage

# S3 method for bess
summary(object, ...)

Arguments

object

A "bess" object.

…

additional print arguments

References

Wen, C., Zhang, A., Quan, S. and Wang, X. (2020). BeSS: An R Package for Best Subset Selection in Linear, Logistic and Cox Proportional Hazards Models, Journal of Statistical Software, Vol. 94(4). doi:10.18637/jss.v094.i04.

See Also

bess.

Examples

# NOT RUN {

#-------------------linear model----------------------#
# Generate simulated data
n <- 200
p <- 20
k <- 5
rho <- 0.4
seed <- 10
Tbeta <- rep(0, p)
Tbeta[1:k*floor(p/k):floor(p/k)] <- rep(1, k)
Data <- gen.data(n, p, k, rho, family = "gaussian", beta = Tbeta, seed = seed)
lm.bss <- bess(Data$x, Data$y, method = "sequential")
lambda.list <- exp(seq(log(5), log(0.1), length.out = 10))
lm.bsrr <- bess(Data$x, Data$y, type = "bsrr", method = "pgsection")

summary(lm.bss)
summary(lm.bsrr)

#-------------------group selection----------------------#
beta <- rep(c(rep(1,2),rep(0,3)), 4)
Data <- gen.data(200, 20, 5, rho=0.4, beta = beta, snr = 100, seed =10)

group.index <- c(rep(1, 2), rep(2, 3), rep(3, 2), rep(4, 3),
                rep(5, 2), rep(6, 3), rep(7, 2), rep(8, 3))
lm.group <- bess(Data$x, Data$y, s.min=1, s.max = 8, type = "bss", group.index = group.index)
lm.groupbsrr <- bess(Data$x, Data$y, type = "bsrr", s.min = 1, s.max = 8, group.index = group.index)

summary(lm.group)
summary(lm.groupbsrr)

#-------------------summary for bess.one----------------------#
Data <- gen.data(n, p, k, rho, family = "gaussian", beta = Tbeta, seed = seed)
lm.bss <- bess.one(Data$x, Data$y, s = 5)
lm.bsrr <- bess.one(Data$x, Data$y, type = "bsrr", s = 5, lambda = 0.01)

summary(lm.bss)
summary(lm.bsrr)

# }