Description Usage Arguments Value Constraints See Also Examples
glm
performs logistic and poisson regression on FLTable objects.
1 |
formula |
A symbolic description of model to be fitted |
data |
An object of class FLTable |
family |
Can be one of poisson,binomial,logisticwt or multinomial characters. Can be family functions like stats::poisson wherever possible. |
catToDummy |
Transform categorical variables to numerical values either using dummy variables or by using Empirical Logit. If the value is 1, transformation is done using dummy variables, else if the value is 0, transformation is done using Empirical Logit. |
performNorm |
0/1 indicating whether to perform standardization of data. |
performVarReduc |
0/1. If the value is 1, the stored procedure eliminates variables based on standard deviation and correlation. |
makeDataSparse |
If 0,Retains zeroes and NULL values from the input table. If 1, Removes zeroes and NULL. If 2,Removes zeroes but retains NULL values. |
minStdDev |
Minimum acceptable standard deviation for elimination of variables. Any variable that has a standard deviation below this threshold is eliminated. This parameter is only consequential if the parameter PerformVarReduc = 1. Must be >0. |
maxCorrel |
Maximum acceptable absolute correlation between a pair of columns for eliminating variables. If the absolute value of the correlation exceeds this threshold, one of the columns is not transformed. Again, this parameter is only consequential if the parameter PerformVarReduc = 1. Must be >0 and <=1. |
classSpec |
list describing the categorical dummy variables. |
whereconditions |
takes the where_clause as a string. |
pThreshold |
The threshold for False positive value that a user can specify to calculate the false positives and false negatives. Must be between 0 and 1. |
pRefLevel |
Reference value for dependent variable in case of multinomial family. |
maxiter |
maximum number of iterations. |
glm
returns FLLogRegrMN
object for
multinomial
family and FLLogRegr
otherwise
The anova method is not yet available for FLLogRegr.
In case of multinomial family, residuals,fitted.values
properties are not available.plot,influence methods are
also not available.
Properties like print(fit$x),model,plot
might take time as they
have to fetch data
glm
for R reference implementation.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | deeptable <- FLTable(getTestTableName("tblLogRegr"),"ObsID","VarID","Num_Val",
whereconditions="ObsID<7001")
glmfit <- glm(NULL,data=deeptable)
coef(glmfit)
summary(glmfit)
head(residuals(glmfit))
plot(glmfit)
glmfit <- glm(NULL,data=deeptable,family="logisticwt",eventweight=0.8,noneventweight=1)
summary(glmfit)
plot(glmfit)
connection <- flConnect(odbcSource = "Gandalf",database = "FL_DEV")
widetable <- FLTable("siemenswidetoday1", "ObsID")
poissonfit <- glm(event ~ meanTemp, family=poisson, data=widetable,offset="age")
summary(poissonfit)
plot(poissonfit)
predData <- FLTable(getTestTableName("preddata1"),"ObsID")
mu <- predict(poissonfit,newdata=predData)
deeptable <- FLTable(getTestTableName("tblLogRegrMN10000"),"ObsID","VarID","Num_Val",
whereconditions="ObsID<7001")
glmfit <- glm(NULL,data=deeptable,family="multinomial")
glmfit$coefficients
glmfit$FLLogRegrStats
glmfit$FLCoeffStdErr
summary(glmfit)
print(glmfit)
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