Commit a2359bc7 authored by Dirk Eddelbuettel's avatar Dirk Eddelbuettel

Import Upstream version 1.3-13

parent d3f21f57
Package: mgcv
Version: 1.3-12
Version: 1.3-13
Author: Simon Wood <simon.wood@r-project.org>
Maintainer: Simon Wood <simon.wood@r-project.org>
Title: GAMs with GCV smoothness estimation and GAMMs by REML/PQL
......@@ -12,4 +12,4 @@ Imports: graphics, stats
Suggests: nlme (>= 3.1-64), MASS (>= 7.2-2)
LazyLoad: yes
License: GPL version 2 or later
Packaged: Tue Dec 13 21:38:39 2005; simon
Packaged: Mon Jan 23 17:09:30 2006; simon
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......@@ -2878,8 +2878,8 @@ summary.gam <- function (object, dispersion = NULL, freq = TRUE, ...)
V <- covmat[start:stop,start:stop] # cov matrix for smooth
p<-object$coefficients[start:stop] # params for smooth
M1<-object$smooth[[i]]$df
M<-round(sum(object$edf[start:stop]))
V<-pinv(V,M1) # get rank M pseudoinverse of V
M<-min(M1,ceiling(2*sum(object$edf[start:stop]))) ## upper limit of 2*edf on rank
V<-pinv(V,M) # get rank M pseudoinverse of V
chi.sq[i]<-t(p)%*%V%*%p
er<-names(object$coefficients)[start]
er<-substring(er,1,nchar(er)-2)
......
1.3-13
* some doc changes
* The p-values for smooth terms had too low power sometimes. Modified
testing procedure so that testing rank is at most
ceiling(2*edf.for.term). This gives quite close to uniform p-value
distributions when the null is true, in simulations, without excessive
inflation of the p-values, relative to parametetric equivalents when
it is not. Still not really satisfactory.
1.3-12
* vis.gam could fail if the original model formula contained functions of
......
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File moved
......@@ -49,11 +49,12 @@ with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
Wood, S.N. (in press) Stable and efficient multiple smoothing parameter estimation for
generalized additive models. J. Amer. Statist. Ass.
Wood, S.N. (2004) Stable and efficient multiple smoothing parameter estimation for
generalized additive models. J. Amer. Statist. Ass. 99:637-686
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -31,21 +31,20 @@ printing method.
P-values are usually reliable if the smoothing parameters are known, or
the model is unpenalized. If smoothing parameters have been estimated then the
p-values are typically somewhat too low. i.e. terms that appear `not
significant' really are not, while terms that are significant, may in fact be
non-significant if the p-value is close to whatever significance level you
are choosing to operate at. This occurs because the uncertainty associated
p-values are typically somewhat too low under the null. This occurs because the uncertainty associated
with the smoothing parameters is neglected in the calculations of the
distributions under the null, which tends to lead to underdispersion in these
distributions, and in turn to p-value estimates that are too low. (In
simulations where the null is correct, I have seen p-values that are as low as half of what they should
be.)
be.) Note however that tests can have low power if the estimated rank of the test
statistic is much higher than the EDF, so that p-values can also be too low in
some cases.
If it is important to have p-values that are as accurate as possible, then,
at least in the single model case, it is probably advisable to perform tests using unpenalized smooths
(i.e. \code{s(...,fx=TRUE)}) with the basis dimension, \code{k}, left at what would
have been used with penalization. Such tests are not as powerful, of
course, but the p-values are more accurate. Whether or not extra accuracy is
course, but the p-values are more accurate under the null. Whether or not extra accuracy is
required will usually depend on whether or not hypothesis testing is a key
objective of the analysis.
}
......@@ -64,7 +63,7 @@ which is in fact an object returned from \code{\link{summary.gam}}.
\author{ Simon N. Wood \email{simon.wood@r-project.org} with substantial
improvements by Henric Nilsson.}
\section{WARNING }{ P-values may be under-estimates, as a result of ignoring
\section{WARNING}{ P-values are only approximate, particularly as a result of ignoring
smoothing parameter uncertainty.
}
......
......@@ -32,7 +32,7 @@ is `too far' from any datum.
}
\references{
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -69,11 +69,10 @@ Pinheiro J.C. and Bates, D.M. (2000) Mixed effects Models in S and S-PLUS. Sprin
For details of how GAMMs are set up here for estimation using \code{lme} see:
Wood, S.N. (2004) Low rank scale invariant tensor product smooths for
Generalized Additive Mixed Models. Technical report of the statistics
department, University of Glasgow.
Wood, S.N. (2006) Low rank scale invariant tensor product smooths for
Generalized Additive Mixed Models. Biometrics
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
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......@@ -38,11 +38,10 @@ Pinheiro J.C. and Bates, D.M. (2000) Mixed effects Models in S and S-PLUS. Sprin
For details of how GAMMs are set up here for estimation using \code{lme} see:
Wood, S.N. (2004) Low rank scale invariant tensor product smooths for
Generalized Additive Mixed Models. Technical report of the statistics
department, University of Glasgow.
Wood, S.N. (2006) Low rank scale invariant tensor product smooths for
Generalized Additive Mixed Models. Biometrics
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
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......@@ -315,9 +315,10 @@ Wood, S.N. (2004b) On confidence intervals for GAMs based on penalized
regression splines. Technical Report 04-12 Department of Statistics,
University of Glasgow.
Wood, S.N. (2004c) Low rank scale invariant tensor product smooths for
generalized additive mixed models. Technical Report 04-13 Department of Statistics,
University of Glasgow.
Wood, S.N. (2006) Low rank scale invariant tensor product smooths for
generalized additive mixed models. Biometrics
Wood S.N. (2006) Generalized Additive Models: An Introduction with R. CRC Press.
Key Reference on GAMs and related models:
......@@ -346,7 +347,7 @@ Wood (2001) mgcv:GAMs and Generalized Ridge Regression for R. R News 1(2):20-25
Wood and Augustin (2002) GAMs with integrated model selection using penalized regression splines and applications
to environmental modelling. Ecological Modelling 157:157-177
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}
......
......@@ -76,7 +76,7 @@ with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -135,7 +135,7 @@ Wood, S.N. (2004) Stable and efficient multiple smoothing parameter estimation f
generalized additive models. J. Amer. Statist. Ass.
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
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......@@ -104,7 +104,7 @@ of the families as described in \code{\link{fix.family.link}}.
O 'Sullivan, Yandall & Raynor (1986) Automatic smoothing of regression
functions in generalized linear models. J. Amer. Statist. Assoc. 81:96-103.
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}
......
......@@ -129,7 +129,7 @@ Wood, S.N. (2004) Stable and efficient multiple smoothing parameter estimation f
generalized additive models. J. Amer. Statist. Ass.
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
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......@@ -54,7 +54,7 @@ and is here termed `outer' iteration.
O 'Sullivan, Yandall & Raynor (1986) Automatic smoothing of regression
functions in generalized linear models. J. Amer. Statist. Assoc. 81:96-103.
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -58,7 +58,7 @@ with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\examples{
......
......@@ -19,7 +19,7 @@ with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
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......@@ -43,7 +43,7 @@ was first proposed in O'Sullivan et al. (1986).
O 'Sullivan, Yandall & Raynor (1986) Automatic smoothing of regression
functions in generalized linear models. J. Amer. Statist. Assoc. 81:96-103.
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -186,9 +186,8 @@ Wood, S.N. (2004) On confidence intervals for GAMs based on penalized
regression splines. Technical Report 04-12 Department of Statistics,
University of Glasgow.
Wood, S.N. (2004) Low rank scale invariant tensor product smooths for
generalized additive mixed models. Technical Report 04-13 Department of Statistics,
University of Glasgow.
Wood, S.N. (2006) Low rank scale invariant tensor product smooths for
generalized additive mixed models. Biometrics.
Key Reference on GAMs and related models:
......
......@@ -180,14 +180,13 @@ generalized additive models. Journal of the American Statistical Association. 99
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
Wood, S.N. (2004b) Low rank scale invariant tensor product smooths for
Generalized Additive Mixed Models. Technical Report of the Department of
Statistics, University of Glasgow, UK.
Wood, S.N. (2006) Low rank scale invariant tensor product smooths for
Generalized Additive Mixed Models. Biometrics.
Wang, Y. (1998) Mixed effects smoothing spline analysis of variance. J.R. Statist. Soc. B 60, 159-174
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -16,7 +16,7 @@ Wood, S.N. (2006) Low rank scale invariant tensor product smooths for
Generalized Additive Mixed Models. Biometrics
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -21,7 +21,7 @@ function returns \code{NULL}.}
\value{The evaluated variable, or \code{NULL}}
\references{
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org} }
......
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......@@ -9,7 +9,7 @@ it as a formula, and interprets the smooth parts of the model formula.
Not normally called directly.
}
\useage{interpret.gam(gf)}
\usage{interpret.gam(gf)}
\arguments{\item{gf}{A GAM formula as supplied to \code{\link{gam}} or \code{\link{gamm}}.}
......@@ -40,7 +40,7 @@ with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
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......@@ -168,7 +168,7 @@ Note that some further useful quantities can be obtained using \code{\link{magic
Wood, S.N. (2004) Stable and efficient multiple smoothing parameter estimation for
generalized additive models. J. Amer. Statist. Ass. 99:673-686
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......@@ -185,7 +185,7 @@ x0 <- runif(n, 0, 1);x1 <- runif(n, 0, 1)
x2 <- runif(n, 0, 1);x3 <- runif(n, 0, 1)
f <- 2 * sin(pi * x0)
f <- f + exp(2 * x1) - 3.75887
f <- f+0.2*x2^11*(10*(1-x2))^6+10*(10*x2)^3*(1-x2)^10-1.396
f <- f+0.2*x2^11*(10*(1-x2))^6+10*(10*x2)^3*(1-x2)^10
e <- rnorm(n, 0, sqrt(sig2))
y <- f + e
# set up additive model
......
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......@@ -139,7 +139,7 @@ Wood, S.N. (2000) Modelling and Smoothing Parameter Estimation
with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -31,7 +31,7 @@ the Newton method. SIAM J. Sci. Statist. Comput. 12:383-398
Wood, S.N. (2000) Modelling and Smoothing Parameter Estimation
with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
......@@ -40,7 +40,7 @@ Wood, S.N. (1994) Monotonic smoothing splines fitted by cross validation SIAM
Journal on Scientific Computing 15(5):1126-1133
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org} }
......
File mode changed from 100644 to 100755
......@@ -21,7 +21,7 @@ so that there is no clash.}
\value{A name that is not in \code{old.names}.}
\references{
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org} }
......
......@@ -39,7 +39,7 @@ notLog(x)
\references{
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
......@@ -60,7 +60,7 @@ notLog2(x,d=.Options$mgcv.vc.logrange,b=1/d)
\references{
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
......@@ -43,7 +43,7 @@ null.space.dimension(d,m)
\references{
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
......@@ -81,7 +81,7 @@ Press, London.
Wood, S.N. (1994) Monotonic smoothing splines fitted by cross validation SIAM
Journal on Scientific Computing 15(5):1126-1133
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -54,7 +54,7 @@ Pinheiro J.C. and Bates, D.M. (2000) Mixed effects Models in S and S-PLUS. Sprin
The \code{nlme} source code.
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
......@@ -64,7 +64,7 @@ Pinheiro J.C. and Bates, D.M. (2000) Mixed effects Models in S and S-PLUS. Sprin
The \code{nlme} source code.
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
......@@ -22,7 +22,7 @@ even coverage, where even means having approximately the same number of data bet
\value{ An array of knot locations.
}
\references{
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
......@@ -136,7 +136,7 @@ Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
Wood, S.N. (2004) Stable and efficient multiple smoothing parameter estimation for
generalized additive models. J. Amer. Statist. Ass. 99:637-686
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}
......
......@@ -110,6 +110,9 @@ with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
Wood, S.N. (2004) Stable and efficient multiple smoothing parameter estimation for
generalized additive models. J. Amer. Statist. Ass. 99:637-686
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}
......
......@@ -19,9 +19,9 @@ with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon@state.gla.ac.uk}}
\author{ Simon N. Wood \email{simon.wood@r-project.org} }
......
File mode changed from 100644 to 100755
......@@ -86,7 +86,7 @@ with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
......@@ -123,15 +123,16 @@ with Multiple Quadratic Penalties. J.R.Statist.Soc.B 62(2):413-428
Wood, S.N. (2003) Thin plate regression splines. J.R.Statist.Soc.B 65(1):95-114
Wood, S.N. (in press) Stable and efficient multiple smoothing parameter estimation for
generalized additive models. J. Amer. Statist. Ass.
Wood, S.N. (2004a) Stable and efficient multiple smoothing parameter estimation for
generalized additive models. J. Amer. Statist. Ass. 99:673-686
The p-spline code given in the example is based on:
Eilers, P.H.C. and B.D. Marx (1996) Flexible Smoothing with B-splines and Penalties.
Statistical Science, 11(2):89-121
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{Simon N. Wood \email{simon.wood@r-project.org}}
......@@ -141,7 +142,7 @@ Statistical Science, 11(2):89-121
\code{\link{smoothCon}}, \code{\link{PredictMat}}
}
\warnings{User defined smooth objects should avoid having attributes names
\section{WARNING}{User defined smooth objects should avoid having attributes names
\code{"qrc"} or \code{"nCons"} as these are used internally to provide
constraint free parameterizations.}
......
......@@ -55,7 +55,7 @@ The parameterization used by \code{\link{gam}} can be controlled via
\references{
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{Simon N. Wood \email{simon.wood@r-project.org}}
......
File mode changed from 100644 to 100755
......@@ -70,7 +70,8 @@ is the parameter vector for the ith smooth term, and this term has estimated
covariance matrix \eqn{ {\bf V}_i}{V_i} then the
statistic is \eqn{ {\bf p}_i^\prime {\bf V}_i^{k-} {\bf
p}_i}{p_i'V_i^{k-}p_i}, where \eqn{ {\bf V}^{k-}_i}{V_i^{k-}} is the rank k
pseudo-inverse of \eqn{ {\bf V_i}}{V_i}, and k is estimated rank of \eqn{ {\bf V_i}}{V_i}.}
pseudo-inverse of \eqn{ {\bf V_i}}{V_i}, and k is estimated rank of \eqn{
{\bf V_i}}{V_i}.}
\item{s.pv}{An array of approximate p-values for the null hypotheses that each
smooth term is zero. Be warned, these are only approximate. In the case of
......@@ -80,7 +81,9 @@ rank of \eqn{ {\bf V_i}}{V_i}. If the dispersion parameter is unknown (in
which case it will have been estimated) the statistic is compared
to an F distribution with k upper d.f. and lower d.f. given by the residual degrees of freedom for the model .
Typically the p-values will be somewhat too low, because they are conditional
on the smoothing parameters, which are usually uncertain.
on the smoothing parameters, which are usually uncertain, but note that the
statistic can also have low power if the rank, k, is too high relative to the
EDF of the term!
}
\item{se}{array of standard error estimates for all parameter estimates.}
......@@ -153,7 +156,7 @@ regression splines. Technical Report 04-12 Department of Statistics,
University of Glasgow.
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org} with substantial
improvements by Henric Nilsson.}
......@@ -178,7 +181,7 @@ x3 <- runif(n, 0, 1)
pi <- asin(1) * 2
y <- 2 * sin(pi * x0)
y <- y + exp(2 * x1) - 3.75887
y <- y + 0.2 * x2^11 * (10 * (1 - x2))^6 + 10 * (10 * x2)^3 * (1 - x2)^10 - 1.396
y <- y + 0.2 * x2^11 * (10 * (1 - x2))^6 + 10 * (10 * x2)^3 * (1 - x2)^10
e <- rnorm(n, 0, sqrt(abs(sig2)))
y <- y + e
b<-gam(y~s(x0)+s(x1)+s(x2)+s(x3))
......
......@@ -129,12 +129,11 @@ values (defualt).}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
\references{
Wood, S.N. (2004) Low rank scale invariant tensor product smooths for
Generalized Additive Mixed Models. Technical Report of the Department of
Statistics, University of Glasgow, UK.
Wood, S.N. (2006) Low rank scale invariant tensor product smooths for
Generalized Additive Mixed Models. Biometrics
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
......
......@@ -41,7 +41,7 @@ constructing tensor product smooths.
product smooth.
}
\references{
\url{http://www.stats.gla.ac.uk/~simon/}
\url{http://www.maths.bath.ac.uk/~sw283/}
}
\author{ Simon N. Wood \email{simon.wood@r-project.org}}
......
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File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
File mode changed from 100644 to 100755
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