Difference between revisions of "Manuals/calci/LOGNORMDIST"
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*Suppose <math>x</math> is Normally Distributed function, then <math> y=ln(x)</math> also Normally Distributed | *Suppose <math>x</math> is Normally Distributed function, then <math> y=ln(x)</math> also Normally Distributed | ||
*<math> z=exp(y)</math> also Normally Distributed. | *<math> z=exp(y)</math> also Normally Distributed. | ||
− | *Let the Normal Distribution function <math>x</math> and its Mean= <math> | + | *Let the Normal Distribution function <math>x</math> and its Mean= <math>\mu</math>, Standard Deviation = <math>\sigma</math> |
*Then the lognormal cumulative distribution is calculated by:<math>F(x,\mu,\sigma)=\frac{1}{2} \left[1+ erf \left (\frac{ln(x)-μ)}{σ\sqrt{2}}\right)\right ]= \phi\left[\frac{ln(x)-\mu}\sigma}\right ]</math> | *Then the lognormal cumulative distribution is calculated by:<math>F(x,\mu,\sigma)=\frac{1}{2} \left[1+ erf \left (\frac{ln(x)-μ)}{σ\sqrt{2}}\right)\right ]= \phi\left[\frac{ln(x)-\mu}\sigma}\right ]</math> | ||
where <math>erf</math> is the error function,. The error function (also called the Gauss error function) is a special function of sigmoid shape which occurs in probability, statistics and partial differential equations. | where <math>erf</math> is the error function,. The error function (also called the Gauss error function) is a special function of sigmoid shape which occurs in probability, statistics and partial differential equations. |
Revision as of 00:17, 31 December 2013
LOGNORMDIST(x,m,sd)
- is the value , is the mean of ,
- And is the standard deviation of .
Description
- This function gives the value of the cumulative log normal distribution.
- This distribution is the continuous probability distribution.
- Lognomal distribution is also called Galton's distribution.
- A random variable which is log-normally distributed takes only positive real values.
- Suppose is Normally Distributed function, then also Normally Distributed
- also Normally Distributed.
- Let the Normal Distribution function and its Mean= , Standard Deviation =
- Then the lognormal cumulative distribution is calculated by:Failed to parse (syntax error): {\displaystyle F(x,\mu,\sigma)=\frac{1}{2} \left[1+ erf \left (\frac{ln(x)-μ)}{σ\sqrt{2}}\right)\right ]= \phi\left[\frac{ln(x)-\mu}\sigma}\right ]}
where is the error function,. The error function (also called the Gauss error function) is a special function of sigmoid shape which occurs in probability, statistics and partial differential equations.
- And is the Cumulative Distribution function of the Standard Normal distribution.
- This function will give the result as error when
1. Any one of the argument is non-numeric. 2. Suppose or
Examples
- LOGNORMDIST(2,5.4,2.76)=0.044061652
- LOGNORMDIST(10,24.05,12.95)=0.046543186
- LOGNORMDIST(50,87.0036,42.9784)=0.026597569
- LOGNORMDIST(-10,5,2)=NAN