WikiLean Articles · Brain · Recent changes · Proposals · Flags · Stats · About

Diff — Exponential distribution

Revision #2569 → #3167 · back to history

modifiedExponential distributionde6012bcb6ed
FieldFrom #2569To #3167
note`expMeasure r` is the exponential measure on ℝ with rate `r`, defined via `gammaMeasure 1 r`.`expMeasure r` is the exponential measure on ℝ with rate `r`, defined as `gammaMeasure 1 r`.
modifiedScale parameter parametrization61fa8bf9eebf
FieldFrom #2569To #3167
anchors[{"section":"Alternative parametrization","snippet":"The exponential distribution is sometimes parametrized in terms of the scale parameter"},{"type":"math_alttext","value":"{\\displaystyle f(x;\\beta )={\\begin{cases}{\\frac {1}{\\beta }}e^{-x/\\beta }&amp;x\\geq 0,\\\\0&amp;x&lt;0.\\end{cases}}\\qquad \\qquad F(x;\\beta )={\\begin{cases}1-e^{-x/\\beta }&amp;x\\geq 0,\\\\0&amp;x&lt;0.\\end{cases}}}"}][{"section":"Alternative parametrization","snippet":"The exponential distribution is sometimes parametrized in terms of the scale parameter"},{"type":"math_alttext","value":"{\\displaystyle f(x;\\beta )={\\begin{cases}{\\frac {1}{\\beta }}e^{-x/\\beta }&amp;x\\geq 0,\\\\0&amp;x<0.\\end{cases}}\\qquad \\qquad F(x;\\beta )={\\begin{cases}1-e^{-x/\\beta }&amp;x\\geq 0,\\\\0&amp;x<0.\\end{cases}}}"}]
modifiedMedian of exponential distributionb478f7eefab1
FieldFrom #2569To #3167
anchors[{"section":"Mean, variance, moments, and median","snippet":"The median of X is given by"},{"type":"math_alttext","value":"{\\displaystyle \\operatorname {m} [X]={\\frac {\\ln(2)}{\\lambda }}&lt;\\operatorname {E} [X],}"},{"type":"math_alttext","value":"{\\displaystyle \\left|\\operatorname {E} \\left[X\\right]-\\operatorname {m} \\left[X\\right]\\right|={\\frac {1-\\ln(2)}{\\lambda }}&lt;{\\frac {1}{\\lambda }}=\\operatorname {\\sigma } [X],}"}][{"section":"Mean, variance, moments, and median","snippet":"The median of X is given by"},{"type":"math_alttext","value":"{\\displaystyle \\operatorname {m} [X]={\\frac {\\ln(2)}{\\lambda }}<\\operatorname {E} [X],}"},{"type":"math_alttext","value":"{\\displaystyle \\left|\\operatorname {E} \\left[X\\right]-\\operatorname {m} \\left[X\\right]\\right|={\\frac {1-\\ln(2)}{\\lambda }}<{\\frac {1}{\\lambda }}=\\operatorname {\\sigma } [X],}"}]
modifiedMemorylessness relation08f2c75d5713
FieldFrom #2569To #3167
anchors[{"section":"Memorylessness property of exponential random variable","snippet":"An exponentially distributed random variable T obeys the relation"},{"type":"math_alttext","value":"{\\displaystyle \\Pr \\left(T&gt;s+t\\mid T&gt;s\\right)=\\Pr(T&gt;t),\\qquad \\forall s,t\\geq 0.}"}][{"section":"Memorylessness property of exponential random variable","snippet":"An exponentially distributed random variable T obeys the relation"},{"type":"math_alttext","value":"{\\displaystyle \\Pr \\left(T>s+t\\mid T>s\\right)=\\Pr(T>t),\\qquad \\forall s,t\\geq 0.}"}]
modifiedQuantile functionef5e68f29055
FieldFrom #2569To #3167
anchors[{"section":"Quantiles","snippet":"The quantile function (inverse cumulative distribution function) for Exp"},{"type":"math_alttext","value":"{\\displaystyle F^{-1}(p;\\lambda )={\\frac {-\\ln(1-p)}{\\lambda }},\\qquad 0\\leq p&lt;1}"}][{"section":"Quantiles","snippet":"The quantile function (inverse cumulative distribution function) for Exp"},{"type":"math_alttext","value":"{\\displaystyle F^{-1}(p;\\lambda )={\\frac {-\\ln(1-p)}{\\lambda }},\\qquad 0\\leq p<1}"}]
modifiedSum of two independent exponentials density06ce66fe3a4e
FieldFrom #2569To #3167
anchors[{"section":"Sum of two independent exponential random variables","snippet":"are independent exponential random variables with respective rate parameters"},{"type":"math_alttext","value":"{\\displaystyle {\\begin{aligned}f_{Z}(z)&amp;=\\int _{-\\infty }^{\\infty }f_{X_{1}}(x_{1})f_{X_{2}}(z-x_{1})\\,dx_{1}\\\\&amp;=\\int _{0}^{z}\\lambda _{1}e^{-\\lambda _{1}x_{1}}\\lambda _{2}e^{-\\lambda _{2}(z-x_{1})}\\,dx_{1}\\\\&amp;=\\lambda _{1}\\lambda _{2}e^{-\\lambda _{2}z}\\int _{0}^{z}e^{(\\lambda _{2}-\\lambda _{1})x_{1}}\\,dx_{1}\\\\&amp;={\\begin{cases}{\\dfrac {\\lambda _{1}\\lambda _{2}}{\\lambda _{2}-\\lambda _{1}}}\\left(e^{-\\lambda _{1}z}-e^{-\\lambda _{2}z}\\right)&amp;{\\text{ if }}\\lambda _{1}\\neq \\lambda _{2}\\\\[4pt]\\lambda ^{2}ze^{-\\lambda z}&amp;{\\text{ if }}\\lambda _{1}=\\lambda _{2}=\\lambda .\\end{cases}}\\end{aligned}}}"},{"type":"math_alttext","value":"{\\displaystyle {\\begin{aligned}H(Z)&amp;=1+\\gamma +\\ln \\left({\\frac {\\lambda _{1}-\\lambda _{2}}{\\lambda _{1}\\lambda _{2}}}\\right)+\\psi \\left({\\frac {\\lambda _{1}}{\\lambda _{1}-\\lambda _{2}}}\\right),\\end{aligned}}}"}][{"section":"Sum of two independent exponential random variables","snippet":"are independent exponential random variables with respective rate parameters"},{"type":"math_alttext","value":"{\\displaystyle {\\begin{aligned}f_{Z}(z)&amp;=\\int _{-\\infty }^{\\infty }f_{X_{1}}(x_{1})f_{X_{2}}(z-x_{1})\\,dx_{1}\\\\&amp;=\\int _{0}^{z}\\lambda _{1}e^{-\\lambda _{1}x_{1}}\\lambda _{2}e^{-\\lambda _{2}(z-x_{1})}\\,dx_{1}\\\\&amp;=\\lambda _{1}\\lambda _{2}e^{-\\lambda _{2}z}\\int _{0}^{z}e^{(\\lambda _{2}-\\lambda _{1})x_{1}}\\,dx_{1}\\\\&amp;={\\begin{cases}{\\dfrac {\\lambda _{1}\\lambda _{2}}{\\lambda _{2}-\\lambda _{1}}}\\left(e^{-\\lambda _{1}z}-e^{-\\lambda _{2}z}\\right)&amp;{\\text{ if }}\\lambda _{1}\\neq \\lambda _{2}\\\\[4pt]\\lambda ^{2}ze^{-\\lambda z}&amp;{\\text{ if }}\\lambda _{1}=\\lambda _{2}=\\lambda .\\end{cases}}\\end{aligned}}}"},{"type":"math_alttext","value":"{\\displaystyle {\\begin{aligned}H(Z)&amp;=1+\\gamma +\\ln \\left({\\frac {\\lambda _{1}-\\lambda _{2}}{\\lambda _{1}\\lambda _{2}}}\\right)+\\psi \\left({\\frac {\\lambda _{1}}{\\lambda _{1}-\\lambda _{2}}}\\right),\\end{aligned}}"}]
modifiedExact confidence interval6ed0948e3c77
FieldFrom #2569To #3167
anchors[{"section":"Confidence intervals","snippet":"An exact 100(1 − α)% confidence interval for the rate parameter of an exponential distribution is given by"},{"type":"math_alttext","value":"{\\displaystyle {\\frac {2n}{{\\widehat {\\lambda }}_{\\textrm {mle}}\\chi _{{\\frac {\\alpha }{2}},2n}^{2}}}&lt;{\\frac {1}{\\lambda }}&lt;{\\frac {2n}{{\\widehat {\\lambda }}_{\\textrm {mle}}\\chi _{1-{\\frac {\\alpha }{2}},2n}^{2}}}\\,,}"},{"type":"math_alttext","value":"{\\displaystyle {\\frac {2n{\\overline {x}}}{\\chi _{{\\frac {\\alpha }{2}},2n}^{2}}}&lt;{\\frac {1}{\\lambda }}&lt;{\\frac {2n{\\overline {x}}}{\\chi _{1-{\\frac {\\alpha }{2}},2n}^{2}}}\\,,}"},{"type":"math_alttext","value":"{\\displaystyle {\\begin{aligned}\\lambda _{\\text{lower}}&amp;={\\widehat {\\lambda }}\\left(1-{\\frac {1.96}{\\sqrt {n}}}\\right)\\\\\\lambda _{\\text{upper}}&amp;={\\widehat {\\lambda }}\\left(1+{\\frac {1.96}{\\sqrt {n}}}\\right)\\end{aligned}}}"}][{"section":"Confidence intervals","snippet":"An exact 100(1 − α)% confidence interval for the rate parameter of an exponential distribution is given by"},{"type":"math_alttext","value":"{\\displaystyle {\\frac {2n}{{\\widehat {\\lambda }}_{\\textrm {mle}}\\chi _{{\\frac {\\alpha }{2}},2n}^{2}}}<{\\frac {1}{\\lambda }}<{\\frac {2n}{{\\widehat {\\lambda }}_{\\textrm {mle}}\\chi _{1-{\\frac {\\alpha }{2}},2n}^{2}}}\\,,}"},{"type":"math_alttext","value":"{\\displaystyle {\\frac {2n{\\overline {x}}}{\\chi _{{\\frac {\\alpha }{2}},2n}^{2}}}<{\\frac {1}{\\lambda }}<{\\frac {2n{\\overline {x}}}{\\chi _{1-{\\frac {\\alpha }{2}},2n}^{2}}}\\,,}"},{"type":"math_alttext","value":"{\\displaystyle {\\begin{aligned}\\lambda _{\\text{lower}}&amp;={\\widehat {\\lambda }}\\left(1-{\\frac {1.96}{\\sqrt {n}}}\\right)\\\\\\lambda _{\\text{upper}}&amp;={\\widehat {\\lambda }}\\left(1+{\\frac {1.96}{\\sqrt {n}}}\\right)\\end{aligned}}"}]
modifiedNormal approximation CI9399517d4046
FieldFrom #2569To #3167
anchors[{"section":"Confidence intervals","snippet":"A simple approximation to the exact interval endpoints can be derived using a normal approximation"},{"type":"math_alttext","value":"{\\displaystyle {\\frac {2n}{{\\widehat {\\lambda }}_{\\textrm {mle}}\\chi _{{\\frac {\\alpha }{2}},2n}^{2}}}&lt;{\\frac {1}{\\lambda }}&lt;{\\frac {2n}{{\\widehat {\\lambda }}_{\\textrm {mle}}\\chi _{1-{\\frac {\\alpha }{2}},2n}^{2}}}\\,,}"},{"type":"math_alttext","value":"{\\displaystyle {\\frac {2n{\\overline {x}}}{\\chi _{{\\frac {\\alpha }{2}},2n}^{2}}}&lt;{\\frac {1}{\\lambda }}&lt;{\\frac {2n{\\overline {x}}}{\\chi _{1-{\\frac {\\alpha }{2}},2n}^{2}}}\\,,}"},{"type":"math_alttext","value":"{\\displaystyle {\\begin{aligned}\\lambda _{\\text{lower}}&amp;={\\widehat {\\lambda }}\\left(1-{\\frac {1.96}{\\sqrt {n}}}\\right)\\\\\\lambda _{\\text{upper}}&amp;={\\widehat {\\lambda }}\\left(1+{\\frac {1.96}{\\sqrt {n}}}\\right)\\end{aligned}}}"}][{"section":"Confidence intervals","snippet":"A simple approximation to the exact interval endpoints can be derived using a normal approximation"},{"type":"math_alttext","value":"{\\displaystyle {\\frac {2n}{{\\widehat {\\lambda }}_{\\textrm {mle}}\\chi _{{\\frac {\\alpha }{2}},2n}^{2}}}<{\\frac {1}{\\lambda }}<{\\frac {2n}{{\\widehat {\\lambda }}_{\\textrm {mle}}\\chi _{1-{\\frac {\\alpha }{2}},2n}^{2}}}\\,,}"},{"type":"math_alttext","value":"{\\displaystyle {\\frac {2n{\\overline {x}}}{\\chi _{{\\frac {\\alpha }{2}},2n}^{2}}}<{\\frac {1}{\\lambda }}<{\\frac {2n{\\overline {x}}}{\\chi _{1-{\\frac {\\alpha }{2}},2n}^{2}}}\\,,"},{"type":"math_alttext","value":"{\\displaystyle {\\begin{aligned}\\lambda _{\\text{lower}}&amp;={\\widehat {\\lambda }}\\left(1-{\\frac {1.96}{\\sqrt {n}}}\\right)\\\\\\lambda _{\\text{upper}}&amp;={\\widehat {\\lambda }}\\left(1+{\\frac {1.96}{\\sqrt {n}}}\\right)\\end{aligned}}}"}]
addedStandard deviation equals mean4c284ac1cf16
addedMemorylessness via complementary CDF8319da320da7
addedMinimum via complementary CDF572b663d127f
addedMedian-mean inequality for exponential9f0a9caf4e27
addedLog-likelihood derivative0dfbacaa05c4
addedFisher information of rate parameter27f27cce8653