matlab怎么求对数正态分布函数的分位数（反函数）么
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logninv Inverse of the lognormal cumulative distribution function (cdf).
X = logninv(P,MU,SIGMA) returns values at P of the inverse lognormal
cdf with distribution parameters MU and SIGMA. MU and SIGMA are the
mean and standard deviation, respectively, of the associated normal
distribution. The size of X is the common size of the input arguments.
A scalar input functions as a constant matrix of the same size as the
other inputs.
Default values for MU and SIGMA are 0 and 1, respectively.
[X,XLO,XUP] = logninv(P,MU,SIGMA,PCOV,ALPHA) returns confidence bounds
for X when the input parameters MU and SIGMA are estimates. PCOV is a
2-by-2 matrix containing the covariance matrix of the estimated parameters.
ALPHA has a default value of 0.05, and specifies 100*(1-ALPHA)% confidence
bounds. XLO and XUP are arrays of the same size as X containing the lower
and upper confidence bounds.
比如期望0，标准差1的对数正态分布，求1%分位数
输入
logninv(0.01,0,1)
即可
X = logninv(P,MU,SIGMA) returns values at P of the inverse lognormal
cdf with distribution parameters MU and SIGMA. MU and SIGMA are the
mean and standard deviation, respectively, of the associated normal
distribution. The size of X is the common size of the input arguments.
A scalar input functions as a constant matrix of the same size as the
other inputs.
Default values for MU and SIGMA are 0 and 1, respectively.
[X,XLO,XUP] = logninv(P,MU,SIGMA,PCOV,ALPHA) returns confidence bounds
for X when the input parameters MU and SIGMA are estimates. PCOV is a
2-by-2 matrix containing the covariance matrix of the estimated parameters.
ALPHA has a default value of 0.05, and specifies 100*(1-ALPHA)% confidence
bounds. XLO and XUP are arrays of the same size as X containing the lower
and upper confidence bounds.
比如期望0，标准差1的对数正态分布，求1%分位数
输入
logninv(0.01,0,1)
即可
更多追问追答
追问
可是我现在不知道函数当中的那两个参数，怎么办
追答
你是知道分布求分位数还是求一组样本的分位数？前者怎么可能不知道期望和方差？后者用函数prctile
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