CODEWITHSUNDEEP
rdistributiongaussianfitdistrplus
CER
CER

Reputation: 27

Fit Bi-Modal / two-gaussian Distribution To Data Set in R

I have some data sets that look like they are composed of a superposition of two normal distributions forming a bimodal plot. I would like to estimate best fit parameters for the distribution of these data sets. Typically I would use fitdistrplus package but I can't find a distribution function to feed its algorithms.

Can someone point me in the direction of one or suggest how I might do it myself?

Upvotes: 1

Views: 2491

Answers (1)

adkane
adkane

Reputation: 1441

The response to this question looks like it gets at your query. I repeat their code here:

library(mixdist)  

#Build data vector "x" as a mixture of data from 3 Normal Distributions  
x1 <- rnorm(1000, mean=0, sd=2.0)  
x2 <- rnorm(500, mean=9, sd=1.5)  
x3 <- rnorm(300, mean=13, sd=1.0)  
x <- c(x1, x2, x3)  

#Plot a histogram (you'll play around with the value for "breaks" as    
#you zero-in on the fit).   Then build a data frame that has the  
#bucket midpoints and counts.  
breaks <- 30  
his <- hist(x, breaks=breaks)  
df <- data.frame(mid=his$mids, cou=his$counts)  
head(df)  

#The above Histogram shows 3 peaks that might be represented by 3 Normal  
#Distributions.  Guess at the 3 Means in Ascending Order, with a guess for  
#the associated 3 Sigmas and fit the distribution.  
guemea <- c(3, 11, 14)  
guesig <- c(1, 1, 1)  
guedis <- "norm"  
(fitpro <- mix(as.mixdata(df), mixparam(mu=guemea, sigma=guesig), dist=guedis))  

#Plot the results  
plot(fitpro, main="Fit a Probability Distribution")  
grid()  
legend("topright", lty=1, lwd=c(1, 1, 2), c("Original Distribution to be Fit", "Individual Fitted Distributions", "Fitted Distributions Combined"), col=c("blue", "red", rgb(0.2, 0.7, 0.2)), bg="white")  

===========================  


Parameters:  
      pi     mu  sigma  
1 0.5533 -0.565 1.9671  
2 0.2907  8.570 1.6169  
3 0.1561 12.725 0.9987  

Distribution:  
[1] "norm"  

Constraints:  
   conpi    conmu consigma   
  "NONE"   "NONE"   "NONE"

Upvotes: 1

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