how to fit exponential curve such as a*b^t in r?

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input <- "    
     t    y    
    1  5.3    
    2  7.2    
    3  9.6    
    4 12.9    
    5 17.1    
    6 23.2"         
   dat<-read.table(textConnection(input),header=TRUE,sep="")    
   t<-dat[,1]    
   y<-dat[,2]   

`y=3.975*(1.341^t)` is the resule of fit,how can i use `nls` function to get it?
Have you looked at ?nls.
Have you simply tried

nls(y~a*b^t,data=dat)

You can also do a linear regression  on  log(y) ~ A + B* t.
And afterwards transform to the original coefficients.

Berend
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Please do not post in html.
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Read the examples section of

?nls

You probably need to provide a start list of values.

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input <- "    
     t    y    
    1  5.3    
    2  7.2    
    3  9.6    
    4 12.9    
    5 17.1    
    6 23.2"         
   dat<-read.table(textConnection(input),header=TRUE,sep="")    
   t<-dat[,1]    
   y<-dat[,2]   

`y=3.975*(1.341^t)` is the resule of fit,how can i use `nls` function
to get it?
[[alternative HTML version deleted]]

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.