Printing Vocabulary Growth Curves (zipfR)
## S3 method for class 'vgc' print(x, all=FALSE, ...) ## S3 method for class 'vgc' summary(object, ...)
x, object |
an object of class |
all |
if |
... |
other arguments passed on from generic method will be ignored |
NB: implementation details and format of the summary are subject to change in future releases
print.vgc calls the standard print method for
data frames internally, but reduces the data set randomly to
show at most 25 sample sizes (unless all=TRUE).
summary.vgc gives a concise summary of the available vocabulary
growth data in the vgc object, including the number and range
of sample sizes, whether spectrum elements are included, and whether
variances are included.
NULL
Unlike other implementations of the summary method,
summary.vgc only prints a summary on screen and does not return
a special "summary" object.
See the vgc manpage for details on vgc objects.
## load Brown "informative" prose empirical vgc
data(BrownInform.emp.vgc)
## summary, print (random subset) and print all
summary(BrownInform.emp.vgc)
print(BrownInform.emp.vgc)
print(BrownInform.emp.vgc,all=TRUE)
## load Brown informative prose spectrum
## and get estimate a fzm model
data(BrownInform.spc)
fzm <- lnre("fzm",BrownInform.spc,exact=FALSE)
## obtain expected vgc up to 2M tokens
## with spectrum elements up to V_3
## and variances
fzm.vgc <- lnre.vgc(fzm,(1:100)*2e+4,m.max=3,variances=TRUE)
## summary and print
summary(fzm.vgc)
print(fzm.vgc)
print(fzm.vgc,all=TRUE)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.