Description Usage Arguments Value Note Author(s) References See Also Examples
Fits hierarchical semiparametric regression model to t-statistics
1 2 3 4 5 6 7 8 9 | penLik.EMNewton(tstat, x, df, spar = c(10^seq(-1,8,length=30), Inf),
nknots = n.knots(length(tstat)), starts,
tuning.method = c("NIC", "CV"), cv.fold = 5, pen.order=1,
poly.degree=pen.order*2-1, optim.method =
c("nlminb", "BFGS", "CG", "L-BFGS-B", "Nelder-Mead", "SANN", "NR"),
logistic.correction = TRUE, em.iter.max = 10,
em.beta.iter.max = 1, newton.iter.max = 1500,
scale.conv = 0.001, lfdr.conv = 0.001, NPLL.conv = 0.001,
debugging = FALSE, plotit = TRUE, ...)
|
tstat |
A numeric vector t-statistics |
x |
A numeric matrix of covariates, with |
df |
A numeric scalar or vector of degrees of freedom |
spar |
A numeric vector of smoothing parameter lambda |
nknots |
A numeric scalar of number of knots |
starts |
An optional numeric vector of starting values |
tuning.method |
Either |
cv.fold |
A numeric scalar of the fold for cross-validation. Ignored if |
pen.order |
A numeric scalar of the order of derivatives of which squared integration will be used as roughness penalty. |
poly.degree |
A numeric scalar of the degree of B-splines. |
optim.method |
A character scalar specifying the method of optimization. |
logistic.correction |
A logical scalar specifying whether or not the effective number of parameters should be corrected using a logistic curve |
em.iter.max |
A numeric scalar specifying the maximum number of EM iterations. If being |
em.beta.iter.max |
A numeric scalar specifying the maximum number of iterations in the maximization step for the beta parameters in the EM algorithm. If being |
newton.iter.max |
A numeric scalar specifying the maximum number of iterations in Newton method. |
scale.conv |
A small numeric scalar specifying the convergence criterion for the scale parameter. |
lfdr.conv |
A small numeric scalar specifying the convergence criterion for the local false discovery rates. |
NPLL.conv |
A small numeric scalar specifying the convergence criretion for the negative penalized log likelhood. |
debugging |
A logical scalar. If |
plotit |
A locgical scalr specifying whether a plot should be generated. |
... |
Currently not used. |
An list of class hisemit
:
lfdr: |
A numeric vector of local false discovery rates. |
model |
A list of |
scale.fact: |
A list with
where |
pi0: |
A numeric vector of mixing proportions for the central t component |
tuning: |
A list with
|
spar: |
A list with
|
enp: |
A list with
|
fit: |
A list with
|
NPLL: |
A list with
|
When spar is too small, the results need to be treated cautiously. It is advisable to plot the results as a check.
Long Qu rtistician@gmail.com
Long Qu, Dan Nettleton, Jack Dekkers (2012) A hierarchical semiparametric model for incorporating inter-gene relationship information for analysis of genomic data. Biometrics, 68(4):1168-1177
plot.hisemit
, fitted.hisemit
, coef.hisemit
,
vcov.hisemit
, residuals.hisemit
, logLik.hisemit
,
confint.hisemit
, plot.hisemit
,
hisemi-package
, pi0-package
1 | # See the examples for the hisemi-package.
|
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