Get coefficients estimated by maximum likelihood into a stargazer table

Question

Stargazer produces very nice latex tables for lm (and other) objects. Suppose I\'ve fit a model by maximum likelihood. I\'d like stargazer to produce a lm-like table for my es

Answer 1

You need to first instantiate a dummy lm object, then dress it up:

#...
model2.lm = lm(y ~ ., data.frame(y=runif(5), beta=runif(5), scale=runif(5), degrees.freedom=runif(5)))
model2.lm$coefficients <- model2$par
model2.lm$fitted.values <- model2$par["const"] + model2$par["beta"]*df$x
model2.lm$residuals <- df$y - model2.lm$fitted.values
stargazer(model2.lm, se = list(model2.coefs$se), summary=FALSE, type='text')

# ===============================================
#                         Dependent variable:    
#                     ---------------------------
#                                  y             
# -----------------------------------------------
# const                        10.127***         
#                               (0.680)          
#                                                
# beta                         1.995***          
#                               (0.024)          
#                                                
# scale                        3.836***          
#                               (0.393)          
#                                                
# degrees.freedom              3.682***          
#                               (1.187)          
#                                                
# -----------------------------------------------
# Observations                    200            
# R2                             0.965           
# Adjusted R2                    0.858           
# Residual Std. Error       75.581 (df = 1)      
# F Statistic              9.076 (df = 3; 1)     
# ===============================================
# Note:               *p<0.1; **p<0.05; ***p<0.01

(and then of course make sure the remaining summary stats are correct)

Answer 2

I was just having this problem and overcame this through the use of the coef se, and omit functions within stargazer... e.g.

stargazer(regressions, ...
                     coef = list(... list of coefs...),
                     se = list(... list of standard errors...),
                     omit = c(sequence),
                     covariate.labels = c("new names"),
                     dep.var.labels.include = FALSE,
                     notes.append=FALSE), file="")

Answer 3

I don't know how committed you are to using stargazer, but you can try using the broom and the xtable packages, the problem is that it won't give you the standard errors for the optim model

library(broom)
library(xtable)
xtable(tidy(model1))
xtable(tidy(model2))