R: Automatic Time Series Analysis and Forecasting using Ata...
const macros = { "\\R": "\\textsf{R}", "\\code
:3)$freq))
## ex. 4: two 10-item forms, max TIF over (-1, 1), consider item sets
x <- ata(pool, 2, test_len=10, max_use
:3)$freq))
## ex. 4: two 10-item forms, max TIF over (-1, 1), consider item sets
x <- ata(pool, 2, test_len=10, max_use
), consider item sets
x <- ata(pool, 2, len=10, max_use=1, group="group")
x <- ata_obj_relative(x, seq(-1, 1, .5), 'max')
), consider item sets
x <- ata(pool, 2, len=10, max_use=1, group="group")
x <- ata_obj_relative(x, seq(-1, 1, .5), 'max')
method that produces scatter plots of predicted vs observed measurements for the training set.
Value
Function WA returns
method that produces scatter plots of predicted vs observed measurements for the training set.
Value
Function WA returns
: false, macros }); }
return;
AtAR Documentation
Package: WA
Type: Package
Title: While-Alive Loss Rate for Recurrent Event in the Presence of
triangle.
Usage
ata(Triangle, NArow.rm = TRUE, colname.sep = "-",
ata(Triangle, NArow.rm = TRUE, colname.sep = "-",
colname.order=c("ascending","descending"))
Arguments
R: Age to Age factors
ataR Documentation
Age to Age factors
ata(Triangle, NArow.rm = TRUE, colname.sep = "-",
colname.order=c("ascending","descending"))
Arguments
Package: kitchen
Type: Package
Title: Convolutional Kitchen Sinks in R
, { throwOnError: false, macros }); }
return;
AtAR Documentation
Package: ata
Title: Automated Test Assembly
Version: 1.1.1
mod <- wa(SumSST ~., data = ImbrieKipp)
## extract the fitted values
fitted(mod)
of Washington.
Usage
data("WA")
of Washington.
Usage
data("WA")
of Washington.
Usage
data("WA")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.
