Displaying 4 results from an estimated 4 matches for "variablea".
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2009 Jul 15
1
loading multiple .Rdata and preserving variable names
...entially.)
I can load consequently multiple .Rdata files (in which variable names are
identical), but I don't know how to preserve variables from these files or
make them unique.
I would imagine pointing them as in a list:
# loading 2, max. 4 outputs of previous calculations
load(DataSet1) # VariableA is present
load(DataSet2) # VariableA is present, too
# both VraiableA listed and present
DataSet1$VariableA$parameters
DataSet2$VariableA$parameters
But what is the way to feed all variables into a list? Or more generally,
what is an efficient way to work with multiple separate outputs which one...
2010 Sep 22
1
agregar valores a una tablea de SQL
Hola a todos
Estoy aprendiendo a trabajar con el paquete de RMySQL, y a la vez con bases SQL,
así que a lo mejor no es tan complicado.
Quiero agregar valores, que genero en R, a una tabla de SQL más o menos la idea
es:
> ssql<-"INSERT INTO tabla1 (variableA, variableB) VALUES
(''valor1'',''valor2'')"
> dbSendQuery(conec, ssql)
pero entonces se incertan ceros en tabla1, siendo que valor1 y valor2, son las
variables que me guardan el numerito que generé en R... cómo le hago para que
SQL así lo entienda??
M...
2011 Mar 27
1
Bootstrap 95% confidence intervals for splines
There appear to be reports in the literature that transform continuous
independent variablea by the use of splines, e.g., assume the dependent
variable is hot dogs eaten per week (HD) and the independent variable is
waistline (WL), a normal linear regression model would be:
nonconfusing_regression <- lm(HD ~ WL)
One might use a spline,
confusion_inducing_regression_with_spline <...
2012 Apr 26
1
Using the R predict function to forecast a model fit with auto.arima function
.... 0.1145 0.102 0.0798 8047.169
sigma^2 estimated as 2.869e+11: log likelihood=-2265.02
AIC=4540.03 AICc=4540.43 BIC=4555.25
After this, I wanted to make some predictions based on the model suggested
by the auto.arima function. I tried to use the following code to get the
predictions:
variableA.pred<-predict(paulfit, n.ahead=36)
*Error in predict.Arima(paulfit, n.ahead = 36) :
'xreg' and 'newxreg' have different numbers of columns: 1 != 0*>
Now, I have understood, and, according to my research the xreg comes into
play if you add external regressors to your arima...