我正在安装[1,2,3,4]
模型:
glm
)
其中X是5列的矩阵,由于内部数据非常大,因此已应用对数转换(model_poisson<- glm(y~X, family="poisson"
)。
X<- log(X+0.0001)
如何读取估计的系数?
我还需要通过预测访问此模型,我必须将模型拟合80%的数据,并在其他20%的数据上进行测试。
Call:
glm(formula = y ~ X, family = "poisson")
Deviance Residuals:
Min 1Q Median 3Q Max
-298.83 -44.30 -12.06 29.77 1195.29
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.733e+00 5.894e-04 6333.9 <2e-16 ***
Xfemale 5.182e-01 7.667e-05 6759.6 <2e-16 ***
Xmale 9.882e-03 4.329e-05 228.3 <2e-16 ***
Xo 2.170e-01 8.620e-05 2517.5 <2e-16 ***
Xs 7.965e-02 4.736e-05 1681.8 <2e-16 ***
Xt 3.994e-02 4.539e-05 880.1 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 170764926 on 4942 degrees of freedom
Residual deviance: 36935043 on 4937 degrees of freedom
AIC: 36982563
Number of Fisher Scoring iterations: 6
因此我的模型是:
ndata <- length(y)
ntraining <- ceiling(0.8*ndata)
ntest <- ndata-ntraining
training_indices<- sample(1:ndata, ntraining, replace=FALSE)
training_m <- m[training_indices]
training_X<- X[training_indices, ]
training_X<- log(training_X+0.00001)
test_set <- m[-training_indices]
test_X<- X[-training_indices, ]
test_X<-as.data.frame(test_X)
如何使用测试仪?