Hi R community
I have a question. I'll explain my situation. I have to build a climate model
to obtain monthly and annual temperature from 2004 to 2008 from a specif area
in Almeria (Spain). To build this climate model, I will use Multiple
regression. My dependant variable will be monthly and annual temperature and
independant variables will be Latitute, Longitude and Altitude and I will work
with climate data from 10 climate stations distributed in my area of interest.
I have to fit the climate model from the data to get temperature for each
month. And I need to use p-value and r-squared adjusted from the model to
obtain the best fit. I'll put an example. My climate data will be:
V1 V2 V3 V4 V5
1 1 18 3 6 187
2 2 21 6 8 68
3 3 23 9 5 42
4 4 19 8 2 194
5 5 17 3 2 225
(V1 - climate station, V2 - temperature, V3 - Latitude, V4 - Longitude, V5 -
Altitude)
I fit the model to the data
fit(V2~V3+V4+V5, data=clima)
And I get
Call:
lm(formula = V2 ~ V3 + V4 + V5, data = clima)
Residuals:
1 2 3 4 5
0.24684 -0.25200 0.17487 -0.05865 -0.11107
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 22.103408 2.526638 8.748 0.0725 .
V3 0.236477 0.152067 1.555 0.3638
V4 -0.073973 0.169716 -0.436 0.7383
V5 -0.024684 0.006951 -3.551 0.1748
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: 0.4133 on 1 degrees of freedom
Multiple R-squared: 0.9926, Adjusted R-squared: 0.9706
F-statistic: 44.95 on 3 and 1 DF, p-value: 0.1091
P- value for this model is 0.1091
However, I see that variable V4 has a really high p-value, so if I take it out,
my model will have a better p-value. So:
fit2<-lm(V2~V4+V5)
Call:
lm(formula = V2 ~ V4 + V5, data = clima)
Residuals:
1 2 3 4 5
0.28356 -0.21880 0.05952 0.40918 -0.53346
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 25.764478 1.199212 21.485 0.00216 **
V4 -0.278286 0.140452 -1.981 0.18606
V5 -0.034109 0.004451 -7.664 0.01660 *
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
Residual standard error: 0.5403 on 2 degrees of freedom
Multiple R-squared: 0.9748, Adjusted R-squared: 0.9497
F-statistic: 38.74 on 2 and 2 DF, p-value: 0.02516
My new p value for the model is lower, and better. So, this is what I have to
do, I have to import climate data, and build the climate model using those
independant variables that give me the best p-value for the model, and I have
to do it automatic (since this example I did it manual). So, my question after
all this long explanation. Is there a package u order I can download to apply
selection of independent variables using as criteria p-value and adjusted
R-squered, or on the contrary, I have to build what I need by myself. I guess I
can build it by myself but it will take me a while but I would like to know if
there is some package to help to do it faster. Well, thanks in advance.
Lucas
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