r - Solve and find x for normally distributed functions -

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i'm trying solve equation , find value x it. i'm using following code:

mu1 = 0 mu2 = 1 sigma1 = 0.5 sigma2 = 0.6 prior1 = 0.3 prior2 = 0.7  boundary = function(x) {   return(( 1 / sqrt(2 * pi * sigma1)) * exp(-0.5 * ((x - mu1) / sigma1)^2)*prior1) -      ((1 / sqrt(2 * pi * sigma2)) * exp(-0.5 * ((x - mu2) / sigma2)^2)*prior2) } uniroot(boundary, c(-1e+05, 1e+07))

this not give me correct answers. i'm pretty new r , not sure how uniroot works.

  • is there better way solve equation?
  • are there packages available solve (similar matlab's solve() function)?

you can shorten code little bit (and minimize chance of typos) using built-in dnorm() function:

curve(dnorm(x,mean=0,sd=0.5),from=-4,to=4) curve(dnorm(x,mean=0,sd=0.6),add=true,col=2)

if try uniroot() on reasonable range, sensible answers:

uniroot(function(x) dnorm(x,0,0.5)-dnorm(x,0,0.6), c(0,5))  ## 0.546 uniroot(function(x) dnorm(x,0,0.5)-dnorm(x,0,0.6), c(-5,0)) ## -0.546

if try start huge values, calculation going underflow (whether hand or use dnorm(); gaussian goes below r's minimum representable valuable (see ?.machine) between 19 , 20.

dnorm(19,0,0.5)  ## 2e-314 dnorm(20,0,0.5)  ## 0

in cases can use log=true in dnorm() compute log-probability , use in computations instead, here (as in many bayesian computations) you're bit stuck because have subtract results.


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