_____________________________________________________________________________________________________________
?Site
?Latitude
?Longitude
?Year
?Tot-Prod
?Total_Density
?dmp
?Dendoudi-1
?15.441964
?-13.540179
?2005
?3271.16
?1007
?16993.25
?Dendoudi-2
?15.397321
?-13.611607
?2005
?1616.84
?250
?25376.67
??
??
??
??
??
??
??
_____________________________________________________________________________________________________________
If I made a scatterplotmatrix with the command show below I obtain a matrix (visible in the image) that show which variables is more correlated with dmp data (violet color).
But, if I made a linear model between the dependent variable (dmp) and ?many independent variables
I get different information about the significativity of the variable.
I mean, variables that appear correlated with dependent variable in the matrix result not correlated in the summary of linear model, and vice versa. Have I made a mistake in the interpretation of the result, or not?
Thank you in advance,
Francesco
#command for matrix-plot
dta <-
senegal5[c( ?2,4,5,6,7,8,9,13,15,17,21,
39,44,45)]
dta.r <-
abs(cor(dta))
dta.col
<- dmat.color(dta.r)
dta.o <-
order.single(dta.r)
cpairs(dta,
dta.o, panel.colors=dta.col, gap=.5,
main="Variables Ordered and Colored by
Correlation")
#command for linear model and summary()
a<- lm ( dmp ~ Latitude
+ Longitude + ?Year + ?Tot.Prod + ? ?Herbaceous.Prod.kg.ha. + ?Leaf.Prod + ?Tree.bio ?+ Total_Density ?+ X1st.SpecieDensity.trunk.ha.+
X2nd.SpecieDensity.trunk.ha.+ Herb_Specie_Index1 + ?iNDVI.JASO.
+
RFE.Cum.JASO., data=senegal5 )
summary(a)
Call:
lm(formula = dmp ~
Latitude + Longitude + Year + Tot.Prod + Herbaceous.Prod.kg.ha. +
? ?Leaf.Prod + Tree.bio + Total_Density +
X1st.SpecieDensity.trunk.ha. +
? ?X2nd.SpecieDensity.trunk.ha. +
Herb_Specie_Index1 + iNDVI.JASO. +
? ?RFE.Cum.JASO.,
data = senegal5)
Residuals:
? ?Min
1Q ?Median ? ? ?3Q
Max
-676.49 -195.77 ?-33.06
113.34 ?816.17
Coefficients:
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? Estimate Std. Error
t value Pr(>|t|)
(Intercept) ? ? ? ? ? ? ? ? ?-3.283e+05 ?4.505e+04
-7.288 4.41e-11 ***
Latitude ? ? ? ? ? ? ? ? ? ? -6.100e+01 ?1.990e+02
-0.307 ? 0.7598
Longitude ? ? ? ? ? ? ? ? ? ?-3.617e+02 ?8.639e+01
-4.187 5.60e-05 ***
Year ? ? ? ? ? ? ? ? ? ? ? ? ?1.604e+02 ?2.300e+01
6.973 2.15e-10 ***
Tot.Prod ? ? ? ? ? ? ? ? ? ? -4.893e+00 ?1.565e+02
-0.031 ? 0.9751
Herbaceous.Prod.kg.ha. ? ? ? ?4.905e+00 ?1.565e+02
0.031 ? 0.9751
Leaf.Prod
? ? ? ? ? ? ? ? ?4.842e+00 ?1.565e+02
0.031 ? 0.9754
Tree.bio ? ? ? ? ? ? ? ? ? ? -4.241e+01 ?2.771e+02
-0.153 ? 0.8786
Total_Density ? ? ? ? ? ? ? ?-1.930e+00 ?8.933e-01
-2.160 ? 0.0329 *
X1st.SpecieDensity.trunk.ha. ?1.992e+00
9.246e-01 ? 2.154
0.0333 *
X2nd.SpecieDensity.trunk.ha. ?3.416e+00
1.642e+00 ? 2.080 ? 0.0398 *
Herb_Specie_Index1 ? ? ? ? ? -1.091e+00 ?1.844e+00
-0.592 ? 0.5552
iNDVI.JASO. ? ? ? ? ? ? ? ? ? 8.914e+02 ?6.076e+01
14.670 ?< 2e-16 ***
RFE.Cum.JASO. ? ? ? ? ? ? ? ? 2.525e+00 ?4.529e-01
5.575 1.68e-07 ***
---
Signif. codes: ?0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ?
1
Residual standard
error: 295.3 on 114 degrees of freedom
Multiple R-squared:
0.9206, ? ? Adjusted R-squared: 0.9116
F-statistic: 101.7 on
13 and 114 DF, ?p-value: < 2.2e-16
______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.