Inverse of NORMSDIST function
-
How to find Inverse of NORMSDIST function ie NORMSINV It Returns the inverse of the standard normal cumulative distribution. The distribution has a mean of zero and a standard deviation of one. Syntax double NORMSINV(double probability) Probability is a probability corresponding to the normal distribution.
-
How to find Inverse of NORMSDIST function ie NORMSINV It Returns the inverse of the standard normal cumulative distribution. The distribution has a mean of zero and a standard deviation of one. Syntax double NORMSINV(double probability) Probability is a probability corresponding to the normal distribution.
-
How to find Inverse of NORMSDIST function ie NORMSINV It Returns the inverse of the standard normal cumulative distribution. The distribution has a mean of zero and a standard deviation of one. Syntax double NORMSINV(double probability) Probability is a probability corresponding to the normal distribution.
You should check out http://www.google.com.au/codesearch[^] first when you have a well known function that you want, I had a quick check and there seems to be implementations there.
Peter "Until the invention of the computer, the machine gun was the device that enabled humans to make the most mistakes in the smallest amount of time."
-
You should check out http://www.google.com.au/codesearch[^] first when you have a well known function that you want, I had a quick check and there seems to be implementations there.
Peter "Until the invention of the computer, the machine gun was the device that enabled humans to make the most mistakes in the smallest amount of time."
-
There are multiple implementations there - it is really in your interest to learn how to search for them. I bet you simply typed in "NORMSINV" and just got lots of references to uses of the function, gave up and came back here. You have to be a little creative and try to make the search engine find function definitions. I went to the same page and with my next search came up with several implementations.
Peter "Until the invention of the computer, the machine gun was the device that enabled humans to make the most mistakes in the smallest amount of time."
-
No, that's not what is meant by "inverse". It's the inverse distribution function he's looking for.
I'm the ocean. I'm a giant undertow.
-
How to find Inverse of NORMSDIST function ie NORMSINV It Returns the inverse of the standard normal cumulative distribution. The distribution has a mean of zero and a standard deviation of one. Syntax double NORMSINV(double probability) Probability is a probability corresponding to the normal distribution.
The inverse CDF of the normal distribution doesn't have an analytical form. You can find an approximation here[^]. The other place to look is in the online version of Numerical Recipes[^]. They have an algorithm for the inverse normal CDF. You can also use the following taken from here[^].
What is a good approximation to the inverse of the
cumulative normal distribution function? Mathematically we can
write this as: Find X such that Q(X) = p for any 0 < p < 1.
(Note: this computes an upper tail probability.) Again, it is
not possible to write this as a closed form expression, so we
resort to approximations. Because of the symmetry of the normal distribution,
we need only consider 0 < p < 0.5. If you
have p > 0.5, then apply the algorithm below to q = 1-p,
and then negate the value for X obtained. (This approximation
is also from Abramowitz and Stegun.)t = sqrt[ ln(1/p^2) ]
c\_0 + c\_1\*t + c\_2\*t^2X = t - ------------------------------
1 + d_1*t + d_2*t^2 + d_3*t^3c_0 = 2.515517
c_1 = 0.802853
c_2 = 0.010328
d_1 = 1.432788
d_2 = 0.189269
d_3 = 0.001308See Abramowitz and Stegun; Press, et al.
You should Google a little harder instead of always asking here. These algorithms were worked out a long time ago and have been available for a long time.
I'm the ocean. I'm a giant undertow.
-
The inverse CDF of the normal distribution doesn't have an analytical form. You can find an approximation here[^]. The other place to look is in the online version of Numerical Recipes[^]. They have an algorithm for the inverse normal CDF. You can also use the following taken from here[^].
What is a good approximation to the inverse of the
cumulative normal distribution function? Mathematically we can
write this as: Find X such that Q(X) = p for any 0 < p < 1.
(Note: this computes an upper tail probability.) Again, it is
not possible to write this as a closed form expression, so we
resort to approximations. Because of the symmetry of the normal distribution,
we need only consider 0 < p < 0.5. If you
have p > 0.5, then apply the algorithm below to q = 1-p,
and then negate the value for X obtained. (This approximation
is also from Abramowitz and Stegun.)t = sqrt[ ln(1/p^2) ]
c\_0 + c\_1\*t + c\_2\*t^2X = t - ------------------------------
1 + d_1*t + d_2*t^2 + d_3*t^3c_0 = 2.515517
c_1 = 0.802853
c_2 = 0.010328
d_1 = 1.432788
d_2 = 0.189269
d_3 = 0.001308See Abramowitz and Stegun; Press, et al.
You should Google a little harder instead of always asking here. These algorithms were worked out a long time ago and have been available for a long time.
I'm the ocean. I'm a giant undertow.
73Zeppelin wrote:
You should Google a little harder instead of always asking here
I think it is more of a case of sheer laziness. He's asking about the FDIST function now, and I pointed him to Wolfram's Mathworld.
"The clue train passed his station without stopping." - John Simmons / outlaw programmer "Real programmers just throw a bunch of 1s and 0s at the computer to see what sticks" - Pete O'Hanlon