MATLAB: I am trying to find the cumulative distribution function of the standard normal. I have the value that I will be using the cdf to analyze but cannot figure out the functions to go with it. Can anyone help me find the correct functions/code

cumulative distributionnormal distributionreliability analysisstandard normal

Below is the code I attempted to run..but it isn't recognizing the makedist function.

x = 0.24 mu = 0 sigma = 1

pd = makedist('Normal')

y = cdf(pd,x)

Best Answer

Use matlab's 'erfc' function in place of 'normcdf' if you don't have the Statistics Toolbox according to the formula:

 normcdf(x) = 1/2*erfc(-x/sqrt(2))

Related Solutions

MATLAB: How to go about finding the standard normal probability based on the z-score

doc normcdf
doc normpdf

When you know what you want but not sure the name, try something like

>> lookfor normal
realmin                        - Smallest positive normalized floating point number.
randn                          - Normally distributed pseudorandom numbers.
sprandn                        - Sparse normally distributed random matrix.
surfnorm                       - Surface normals.
isonormals                     - Isosurface normals.
cde                            - cd elliptic function with normalized complex argument.
sne                            - sn elliptic function with normalized complex argument.
addfreqcsmenu                  - Add a cs menu to switch between linear and normalized frequency
convertfrequnits               - converts between Normalized, Hz, kHz, etc
histfit                        - Histogram with superimposed fitted normal density.
jbtest                         - Jarque-Bera hypothesis test of composite normality.
lhsnorm                        - Generate a latin hypercube sample with a normal distribution
logncdf                        - Lognormal cumulative distribution function (cdf).
lognfit                        - Parameter estimates and confidence intervals for lognormal data.
logninv                        - Inverse of the lognormal cumulative distribution function (cdf).
lognlike                       - Negative log-likelihood for the lognormal distribution.
lognpdf                        - Lognormal probability density function (pdf).
lognrnd                        - Random arrays from the lognormal distribution.
lognstat                       - Mean and variance for the lognormal distribution.
mvncdf                         - Multivariate normal cumulative distribution function (cdf).
mvnpdf                         - Multivariate normal probability density function (pdf).
mvnrnd                         - Random vectors from the multivariate normal distribution.
normcdf                        - Normal cumulative distribution function (cdf).
normfit                        - Parameter estimates and confidence intervals for normal data.
norminv                        - Inverse of the normal cumulative distribution function (cdf).
normlike                       - Negative log-likelihood for the normal distribution.
normpdf                        - Normal probability density function (pdf).
normplot                       - Displays a normal probability plot.
normrnd                        - Random arrays from the normal distribution.
normspec                       - Plots normal density between specification limits.
normstat                       - Mean and variance for the normal distribution.
logn3fit                       - Fit a 3-param lognormal dist'n using cumulative probabilities.
wgtnormfit                     - Fitting example for a weighted normal distribution.
wgtnormfit2                    - Fitting example for a weighted normal distribution (log(sigma) parameterization).
>>

Judicious search terms help but seeing the list of things related to "normal" lets you find the two functions of interest (plus a lot more depending upon which toolboxes are available, maybe) that might be of use/interest...

MATLAB: Difference between normcdf and 1-erfc

No. Here is some simple code that creates a plot that illustrates that those two functions are not equal:

x = -5 : 0.01 : 5;
y1 = normcdf(x);
y2 = 1-erfc(x);
figure
plot(x,y1,x,y2)
legend('normcdf','1-erfc')

Best Answer

Related Solutions

MATLAB: How to go about finding the standard normal probability based on the z-score

MATLAB: Difference between normcdf and 1-erfc

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