I just successfully compiled R-1.6.0 on a Red Hat 7.2 machine. When I
tried to install "grid" from source, I got this error. Any
suggestions? I don't think it is a dependency problem. I also attach
the output from library().
Yuelin Li.
-------------> install.packages("grid")
trying URL `http://cran.r-project.org/src/contrib/PACKAGES'
Content type `text/plain; charset=iso-8859-1' length 84585 bytes
opened URL
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downloaded 82Kb
trying URL `http://cran.r-project.org/src/contrib/grid_0.6-1.tar.gz'
Content type `application/x-tar' length 139516 bytes
opened URL
.......... .......... .......... .......... ..........
.......... .......... .......... .......... ..........
.......... .......... .......... ......
downloaded 136Kb
* Installing *source* package 'grid' ...
** libs
gcc -I/usr/local/lib/R/include -I/usr/local/include
-D__NO_MATH_INLINES -mieee-fp -fPIC -g -O2 -c gpar.c -o gpar.o
gcc -I/usr/local/lib/R/include -I/usr/local/include
-D__NO_MATH_INLINES -mieee-fp -fPIC -g -O2 -c grid.c -o grid.o
grid.c: In function `L_text':
grid.c:1091: warning: passing arg 9 of `GEText' makes pointer from
integer without a cast
grid.c:1091: incompatible type for argument 12 of `GEText'
grid.c:1091: too few arguments to function `GEText'
make: *** [grid.o] Error 1
ERROR: compilation failed for package 'grid'
Delete downloaded files (y/N)? y
----- output from library() ----------
Packages in library `/usr/local/lib/R/library':
base The R base package
boot Bootstrap R (S-Plus) Functions (Canty)
class Functions for classification
cluster Functions for clustering (by Rousseeuw et al.)
ctest Classical Tests
eda Exploratory Data Analysis
foreign Read data stored by Minitab, S, SAS, SPSS,
Stata, ...
gregmisc Greg's Miscellaneous Functions
grid The Grid Graphics Package
KernSmooth Functions for kernel smoothing for Wand &
Jones (1995)
lattice Lattice Graphics
lqs Resistant Regression and Covariance Estimation
MASS Main Library of Venables and Ripley's MASS
methods Formal Methods and Classes
mgcv Multiple smoothing parameter estimation and
GAMs by GCV
modreg Modern Regression: Smoothing and Local Methods
mva Classical Multivariate Analysis
nlme Linear and nonlinear mixed effects models
nnet Feed-forward neural networks and multinomial
log-linear models
rpart Recursive partitioning
SASmixed Data sets from "SAS System for Mixed Models"
spatial functions for kriging and point pattern
analysis
splines Regression Spline Functions and Classes
stepfun Step Functions, including Empirical
Distributions
survival Survival analysis, including penalised
likelihood.
tcltk Interface to Tcl/Tk
tools Tools for Package Development and
Administration
ts Time series functions
xgobi Interface to the XGobi and XGvis programs for
graphical data analysis
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