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MeanVarianceC::MeanVarianceC(const SArray1dC &) MeanVarianceC::MeanVarianceC(void) MeanVarianceC::MeanVarianceC(SizeT,RealT,RealT) MeanVarianceC::StdDeviation(void) const MeanVarianceC::Variance(void) const MeanVarianceC::Number(void) const MeanVarianceC::Mean(void) const MeanVarianceC::Probability(RealT,RealT) MeanVarianceC::Gauss(RealT) MeanVarianceC::operator +=(const MeanVarianceC &) MeanVarianceC::operator -=(const MeanVarianceC &) MeanVarianceC::operator *(const MeanVarianceC &) const

MeanVarianceC(const SArray1dC<RealT> & data)

Calculate the mean and variance from an array of numbers.

MeanVarianceC()

Default constructor.

MeanVarianceC(SizeT nn,RealT nmean,RealT nvar)

Constructor.

RealT StdDeviation() const

Get the standard deviation.

RealT Variance() const

Access the variance.

SizeT Number() const

Access the number of samples.

RealT Mean() const

Access the mean.

RealT Probability(RealT low,RealT high)

Find the probability of getting a sample with a values between low and high.

RealT Gauss(RealT x)

Value of the gauss distribution at x.
Also known as the normal distribution.

MeanVarianceC & operator +=(const MeanVarianceC & mv)

Add another MeanVariance to this one.

MeanVarianceC & operator -=(const MeanVarianceC & mv)

Remove another MeanVariance from this one.

MeanVarianceC operator *(const MeanVarianceC & oth) const

Calculate the product of the two probability density functions.
This assumes the estimates of the distributions are accurate. (The number of samples is ignored)