summary.TML | R Documentation |
Summary and print methods
for R
object of class "TML" and print
method for the summary object.
Further, methods fitted
(), residuals
(), weights
()
or update
() work (via the default methods), and coef
(), vcov
()
have explicitly defined TML methods.
## S3 method for class 'TML'
summary(object, ...)
## S3 method for class 'TML'
print(x, digits = max(3, getOption("digits") - 3), ...)
## S3 method for class 'TML'
coef(object, ...)
## S3 method for class 'TML'
vcov(object, ...)
## S3 method for class 'summary.TML'
print(x, digits = max(3, getOption("digits") - 3),
signif.stars = getOption("show.signif.stars"), ...)
object |
An object of class "TML", usually, a result of a call to |
... |
Potentially more arguments passed to methods. |
digits |
Number of digits for printing, see |
x |
An object of class "TML" or "summary.TML". |
signif.stars |
Logical indicating if the P-values should be visualized by so called "significance stars". |
summary.TML
returns an object of class
"summary.TML".
print.TML
returns a printed summary of object of class "TML".
print.summary.TML
tries to be smart about formatting the coefficients, standard errors, etc, and gives "significance stars" if signif.stars is TRUE (as per default when options
where not changed).
coef.TML
returns the final coefficient estimates (value th1
of a "TML" object), and vcov.TML
returns the covariance matrix of the final estimates (value CV1
of a "TML" object).
An object of class "summary.TML" is a list with the following components:
call |
The component from |
terms |
The component from |
residuals |
The component from |
fitted.values |
The component from |
tn |
The component from |
coefficients |
The matrix of coefficients, standard errors, t-values and p-values. Aliased coefficients are omitted. |
aliased |
Named logical vector showing if the original coefficients are aliased. |
df |
Degrees of freedom, a 3-vector (p, n-p, p*), the last being the number of non-aliased coefficients. |
sigma |
The final scale estimate from |
cutoff.values |
A vector of the final lower and upper cut-off values from |
TML.noncensored
, TML.censored
, summary
, print
## Not run:
data(D243)
Cost <- D243$Cost # Cost (Swiss francs)
LOS <- D243$LOS # Length of stay (days)
Adm <- D243$Typadm; Adm <- (Adm==" Urg")*1 # Type of admission
# (0=on notification, 1=Emergency)
Ass <- D243$Typass; Ass <- (Ass=="P" )*1 # Type of insurance
# (0=usual, 1=private)
Age <- D243$age # Age (years)
Dst <- D243$dest; Dst <- (Dst=="DOMI")*1 # Destination
# (1=Home, 0=another hospital)
Sex <- D243$Sexe; Sex <- (Sex=="M" )*1 # Sex (1=Male, 0=Female)
# Truncated maximum likelihood regression with Gaussian errors
z <- TML.noncensored(log(Cost)~log(LOS)+Adm+Ass+Age+Dst+Sex, otp="adaptive",
cov="nonparametric", control=list(fastS=TRUE))
z # -> print.TML(....)
sumz <- summary(z) # -> summary.TML(....)
sumz # -> print.summary.TML(....)
coef(z) # -> coef.TML(....)
vcov(z) # -> vcov.TML(....)
## End(Not run)
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