Good morning,
I am using R to try to model the proportion of burned area in Portugal. 
The dependent variable is the proportion (P). The family used is 
binomial and the epsilon would be binary. They have recommended me to 
use the Betareg package as it allows to work with proportions.

When I use the Betareg function for my data (2800 lines) with 7 
variavels. I created a model using the sum of all seven variables and 
using p (proportion of area burnt as the independent variable). I 
obtained these results, can you tell me if this is normal? or what do 
the errors mean? Thank you in advance.
Is there any limit in the number of lines and variables(columns) to use?

This was the functions used and the results obtained:
 >attach(dados)
 mod9 <- betareg(P ~ 
Fuel+Temperature+Slope+Altitude+Precipitation+Roadsproximity+Population, 
data=dados)
Warning messages:
1: NaNs produced in: sqrt(W)
2: NaNs produced in: sqrt(W)
3: NaNs produced in: sqrt(1 + phihat)
 > summary(mod9)

Call:
betareg(formula = P ~ Fuel + Temperature + Slope + Altitude +     
Precipitation + Roadsproximity + Population, data = dados)

Deviance 	Residuals: 	
	
	

	Min. 	1st 	Qu. 	Median 	3rd

	0 	0 	0 	0 	0

	
	
	
	
	
Coefficients: 	
	
	
	

	
	Estimate 	Std.Error 	z-value 	Pr(>|z|)
(Intercept) 	-83062.5 	9.34E-02 	-8.89E+05 	0
FuelAnnualCrop 	-2256.8 	2.31E-01 	-9.78E+03 	0
FuelHard 	
	-8179.8 	7.95E-02 	-1.03E+05 	0
FuelHardSoftEuc 	-4449.7 	7.02E-02 	-6.34E+04 	0
FuelNoFuel 	-9552.1 	9.02E-02 	-1.06E+05 	0
FuelPermCrop 	-5112.5 	8.39E-02 	-6.10E+04 	0
FuelShrubs 	-8246 	7.32E-02 	-1.13E+05 	0
FuelSoft 	
	-11795.1 	7.51E-02 	-1.57E+05 	0
FuelSoftEuc 	-1561.8 	7.67E-02 	-2.04E+04 	0
Temperature 	-1.3E+07 	7.14E-04 	-1.80E+10 	0
Slope 	
	78122.8 	3.78E-03 	2.07E+07 	0
Altitude 	
	1143023 	7.19E-05 	1.59E+10 	0
Precipitation 	-1482288 	2.11E-03 	-7.03E+08 	0
RoadsproximityDistRd>1Km 	-45315.1 	3.82E-02 	-1.19E+06 	0
Population 	4711684 	2.81E-04 	1.68E+10 	0



Estimated precision parameter (phi): -560353.4 with s.e. 315.9113

    Null Deviance: 0 on 2818 degrees of freedom
Residual Deviance: 0 on 2804 degrees of freedom
Log-Likelihood Ratio Statistic: 3291846935 on 14 degrees of freedom

Pseudo R^2: 0.07753642           AIC: -3291849573

Warning messages:
1: NaNs produced in: sqrt(muhat * (1 - muhat)/(1 + phihat))
2: NaNs produced in: sqrt(muhat * (1 - muhat)/(1 + phihat))

Thank you very much in advance,

Jordi



>


-- 
______________________________________________________________________
Jordi Garcia-Gonzalo  
 
FORCHANGE - Forest Ecosystem Management Under Global Change
Departamento de Engenharia Florestal - Instituto Superior de Agronomia
Universidade Técnica de Lisboa
Tapada da Ajuda, 1349-017 Lisboa 
Portugal
tel: +351 21 365 33 66
fax: +351 21 364 50 00
email:Jordigarcia@isa.utl.pt


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