a=dat2)
#The code below is to replace the NA values with predicted.
#dat1<-within(dat1,{Dischargenew<-ifelse(is.na(Discharge)==T,fit,Discharge)})
#dat1new<-dat1[,c(1:2,4)]
A.K.
- Original Message -
From: cm
To: r-help@r-project.org
Cc:
Sent: Tuesday, July 24, 2012 2:20 P
On Tue, Jul 24, 2012 at 2:06 PM, wrote:
> Yes, why wouldn't I? It's a linear model between two sets of data: x and y.
Conventionally, one predicts y based on x -- which is specified y ~ x,
not x ~ y. (Predictors on the RHS, predicted on the LHS)
>
> Also, what would the new data be if i want to
Yes, why wouldn't I? It's a linear model between two sets of data: x and y.
Also, what would the new data be if i want to predict into the future? So,
for example, the data goes from a month ago to today. I want to predict what
tomorrow's data would be. So what is "newdata"?
--
View this mes
On Jul 24, 2012, at 1:38 PM, cm wrote:
> How do I set it up? Because when I do predict(model) I get a ton of points,
> not just one.
You need to supply newdata= . predict() without new data gives predicted
values for the predictors you for the model to.
Incidentally, repeating Uwe -- are
How do I set it up? Because when I do predict(model) I get a ton of points, not
just one.
- Original Message -
From: "Uwe Ligges-3 [via R]"
Date: Tuesday, July 24, 2012 2:28 pm
Subject: Re: Linear Model Prediction
To: cm
>
>
>
>
> On 24.07.2012 20:20, cm wrote:
> > I have data X a
On 24.07.2012 20:20, cm wrote:
I have data X and Y, and I want to predict what the very next point would be
based off the model. This is what I have:
model=lm(x~y)
Hmmm, are you sure about the above code?
I think I want to use the predict function, but I'm not exactly sure what to
do.
Y
I have data X and Y, and I want to predict what the very next point would be
based off the model. This is what I have:
>model=lm(x~y)
I think I want to use the predict function, but I'm not exactly sure what to
do.
Thank you!
--
View this message in context:
http://r.789695.n4.nabble.com/Line
7 matches
Mail list logo
