R

Install rgdal package on ubuntu

sudo apt-get install libgdal1-dev libproj-dev
R
> install.packages("rgdal")

Embedding R

Reference http://bioconductor.org/help/course-materials/2012/Seattle-Oct-2012/AdvancedR.pdf

mli@PhenomIIx6:~/Downloads/R-2.15.2/library/AdvancedR/embedding$ export R_HOME=/home/mli/Downloads/R-2.15.2
mli@PhenomIIx6:~/Downloads/R-2.15.2/library/AdvancedR/embedding$ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/mli/Downloa       ds/R-2.15.2/lib
mli@PhenomIIx6:~/Downloads/R-2.15.2/library/AdvancedR/embedding$ g++ embed.c -I/home/mli/Downloads/R-2.15.2/include -L/hom       e/mli/Downloads/R-2.15.2/lib -lR -rpath/home/mli/Downloads/R-2.15.2
g++: error: unrecognized option ‘-rpath/home/mli/Downloads/R-2.15.2’
mli@PhenomIIx6:~/Downloads/R-2.15.2/library/AdvancedR/embedding$ g++ embed.c -I/home/mli/Downloads/R-2.15.2/include -L/hom       e/mli/Downloads/R-2.15.2/lib -lR

mli@PhenomIIx6:~/Downloads/R-2.15.2/library/AdvancedR/embedding$ R CMD ./a.out
WARNING: ignoring environment value of R_HOME

R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.


ns> require(stats); require(graphics)

ns> ns(women$height, df = 5)
                 1            2           3          4             5
 [1,] 0.000000e+00 0.000000e+00  0.00000000 0.00000000  0.0000000000
 [2,] 7.592323e-03 0.000000e+00 -0.08670223 0.26010669 -0.1734044626
 [3,] 6.073858e-02 0.000000e+00 -0.15030440 0.45091320 -0.3006088020
 [4,] 2.047498e-01 6.073858e-05 -0.16778345 0.50335034 -0.3355668952
 [5,] 4.334305e-01 1.311953e-02 -0.13244035 0.39732106 -0.2648807067
 [6,] 6.256681e-01 8.084305e-02 -0.07399720 0.22199159 -0.1479943948
 [7,] 6.477162e-01 2.468416e-01 -0.02616007 0.07993794 -0.0532919575
 [8,] 4.791667e-01 4.791667e-01  0.01406302 0.02031093 -0.0135406187
 [9,] 2.468416e-01 6.477162e-01  0.09733619 0.02286023 -0.0152401533
[10,] 8.084305e-02 6.256681e-01  0.27076826 0.06324188 -0.0405213106
[11,] 1.311953e-02 4.334305e-01  0.48059836 0.12526031 -0.0524087186
[12,] 6.073858e-05 2.047498e-01  0.59541597 0.19899261  0.0007809246
[13,] 0.000000e+00 6.073858e-02  0.50097182 0.27551020  0.1627793975
[14,] 0.000000e+00 7.592323e-03  0.22461127 0.35204082  0.4157555879
[15,] 0.000000e+00 0.000000e+00 -0.14285714 0.42857143  0.7142857143
attr(,"degree")
[1] 3
attr(,"knots")
 20%  40%  60%  80%
60.8 63.6 66.4 69.2
attr(,"Boundary.knots")
[1] 58 72
attr(,"intercept")
[1] FALSE
attr(,"class")
[1] "ns"     "basis"  "matrix"

ns> summary(fm1 <- lm(weight ~ ns(height, df = 5), data = women))

Call:
lm(formula = weight ~ ns(height, df = 5), data = women)

Residuals:
     Min       1Q   Median       3Q      Max
-0.38333 -0.12585  0.07083  0.15401  0.30426

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)
(Intercept)         114.7447     0.2338  490.88  < 2e-16 ***
ns(height, df = 5)1  15.9474     0.3699   43.12 9.69e-12 ***
ns(height, df = 5)2  25.1695     0.4323   58.23 6.55e-13 ***
ns(height, df = 5)3  33.2582     0.3541   93.93 8.91e-15 ***
ns(height, df = 5)4  50.7894     0.6062   83.78 2.49e-14 ***
ns(height, df = 5)5  45.0363     0.2784  161.75  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.2645 on 9 degrees of freedom
Multiple R-squared: 0.9998,     Adjusted R-squared: 0.9997
F-statistic:  9609 on 5 and 9 DF,  p-value: < 2.2e-16


ns> ## example of safe prediction
ns> plot(women, xlab = "Height (in)", ylab = "Weight (lb)")

ns> ht <- seq(57, 73, length.out = 200)

ns> lines(ht, predict(fm1, data.frame(height=ht)))

ns> ## Don't show:
ns> ## Consistency:
ns> x <- c(1:3,5:6)

ns> stopifnot(identical(ns(x), ns(x, df = 1)),
ns+           identical(ns(x, df=2), ns(x, df=2, knots=NULL)),# not true till 2.15.2
ns+           !is.null(kk <- attr(ns(x), "knots")),# not true till 1.5.1
ns+           length(kk) == 0)

ns> ## End Don't show
ns>
ns>
ns>


mli@PhenomIIx6:~/Downloads/R-2.15.2/library/AdvancedR/embedding$ R
WARNING: ignoring environment value of R_HOME

R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(splines)
> example("ns")

ns> require(stats); require(graphics)

ns> ns(women$height, df = 5)
                 1            2           3          4             5
 [1,] 0.000000e+00 0.000000e+00  0.00000000 0.00000000  0.0000000000
 [2,] 7.592323e-03 0.000000e+00 -0.08670223 0.26010669 -0.1734044626
 [3,] 6.073858e-02 0.000000e+00 -0.15030440 0.45091320 -0.3006088020
 [4,] 2.047498e-01 6.073858e-05 -0.16778345 0.50335034 -0.3355668952
 [5,] 4.334305e-01 1.311953e-02 -0.13244035 0.39732106 -0.2648807067
 [6,] 6.256681e-01 8.084305e-02 -0.07399720 0.22199159 -0.1479943948
 [7,] 6.477162e-01 2.468416e-01 -0.02616007 0.07993794 -0.0532919575
 [8,] 4.791667e-01 4.791667e-01  0.01406302 0.02031093 -0.0135406187
 [9,] 2.468416e-01 6.477162e-01  0.09733619 0.02286023 -0.0152401533
[10,] 8.084305e-02 6.256681e-01  0.27076826 0.06324188 -0.0405213106
[11,] 1.311953e-02 4.334305e-01  0.48059836 0.12526031 -0.0524087186
[12,] 6.073858e-05 2.047498e-01  0.59541597 0.19899261  0.0007809246
[13,] 0.000000e+00 6.073858e-02  0.50097182 0.27551020  0.1627793975
[14,] 0.000000e+00 7.592323e-03  0.22461127 0.35204082  0.4157555879
[15,] 0.000000e+00 0.000000e+00 -0.14285714 0.42857143  0.7142857143
attr(,"degree")
[1] 3
attr(,"knots")
 20%  40%  60%  80%
60.8 63.6 66.4 69.2
attr(,"Boundary.knots")
[1] 58 72
attr(,"intercept")
[1] FALSE
attr(,"class")
[1] "ns"     "basis"  "matrix"

ns> summary(fm1 <- lm(weight ~ ns(height, df = 5), data = women))

Call:
lm(formula = weight ~ ns(height, df = 5), data = women)

Residuals:
     Min       1Q   Median       3Q      Max
-0.38333 -0.12585  0.07083  0.15401  0.30426

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)
(Intercept)         114.7447     0.2338  490.88  < 2e-16 ***
ns(height, df = 5)1  15.9474     0.3699   43.12 9.69e-12 ***
ns(height, df = 5)2  25.1695     0.4323   58.23 6.55e-13 ***
ns(height, df = 5)3  33.2582     0.3541   93.93 8.91e-15 ***
ns(height, df = 5)4  50.7894     0.6062   83.78 2.49e-14 ***
ns(height, df = 5)5  45.0363     0.2784  161.75  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.2645 on 9 degrees of freedom
Multiple R-squared: 0.9998,     Adjusted R-squared: 0.9997
F-statistic:  9609 on 5 and 9 DF,  p-value: < 2.2e-16


ns> ## example of safe prediction
ns> plot(women, xlab = "Height (in)", ylab = "Weight (lb)")

ns> ht <- seq(57, 73, length.out = 200)

ns> lines(ht, predict(fm1, data.frame(height=ht)))

ns> ## Don't show:
ns> ## Consistency:
ns> x <- c(1:3,5:6)

ns> stopifnot(identical(ns(x), ns(x, df = 1)),
ns+           identical(ns(x, df=2), ns(x, df=2, knots=NULL)),# not true till 2.15.2
ns+           !is.null(kk <- attr(ns(x), "knots")),# not true till 1.5.1
ns+           length(kk) == 0)

ns> ## End Don't show
ns>
ns>
ns>