15:[["$","meta","0",{"name":"viewport","content":"width=device-width, initial-scale=1"}],["$","meta","1",{"charSet":"utf-8"}],["$","title","2",{"children":"gev() R function from [VaRES] | R PACKAGES"}],["$","meta","3",{"name":"description","content":"Computes the pdf, cdf, value at risk and expected shortfall for the generalized extreme value distribution due to Fisher and Tippett (1928) given by [REMOVE_ME]$$ \\begin{array}{ll}&\\displaystylef(x) =\\frac {1}{\\sigma} \\left[ 1 + \\xi \\left( \\frac {x - \\mu}{\\sigma} \\right) \\right]^{-1/\\xi - 1}\\exp \\left\\{ -\\left[ 1 + \\xi \\left( \\frac {x - \\mu}{\\sigma} \\right)\\right]^{-1/\\xi} \\right\\},\\\\&\\displaystyleF(x) = \\exp \\left\\{ -\\left[ 1 + \\xi \\left( \\frac {x - \\mu}{\\sigma} \\right) \\right]^{-1/\\xi} \\right\\},\\\\&\\displaystyle{\\rm VaR}_p (X) = \\mu - \\frac {\\sigma}{\\xi} + \\frac {\\sigma}{\\xi} (-\\log p)^{-\\xi},\\\\&\\displaystyle{\\rm ES}_p (X) = \\mu - \\frac {\\sigma}{\\xi} + \\frac {\\sigma}{p \\xi} \\int_0^p (-\\log v)^{-\\xi} dv\\end{array} [REMOVE_ME_2]$$\n\nfor $x \\geq \\mu - \\sigma / \\xi$ if $\\xi > 0$, $x \\leq \\mu - \\sigma / \\xi$ if $\\xi < 0$, $-\\infty < x < \\infty$ if $\\xi = 0$, $0 < p < 1$, $-\\infty < \\mu < \\infty$, the location parameter, $\\sigma > 0$, the scale parameter, and $-\\infty < \\xi < \\infty$, the shape parameter."}],["$","meta","4",{"property":"og:title","content":"gev() R function from [VaRES]"}],["$","meta","5",{"property":"og:description","content":"Computes the pdf, cdf, value at risk and expected shortfall for the generalized extreme value distribution due to Fisher and Tippett (1928) given by [REMOVE_ME]$$ \\begin{array}{ll}&\\displaystylef(x) =\\frac {1}{\\sigma} \\left[ 1 + \\xi \\left( \\frac {x - \\mu}{\\sigma} \\right) \\right]^{-1/\\xi - 1}\\exp \\left\\{ -\\left[ 1 + \\xi \\left( \\frac {x - \\mu}{\\sigma} \\right)\\right]^{-1/\\xi} \\right\\},\\\\&\\displaystyleF(x) = \\exp \\left\\{ -\\left[ 1 + \\xi \\left( \\frac {x - \\mu}{\\sigma} \\right) \\right]^{-1/\\xi} \\right\\},\\\\&\\displaystyle{\\rm VaR}_p (X) = \\mu - \\frac {\\sigma}{\\xi} + \\frac {\\sigma}{\\xi} (-\\log p)^{-\\xi},\\\\&\\displaystyle{\\rm ES}_p (X) = \\mu - \\frac {\\sigma}{\\xi} + \\frac {\\sigma}{p \\xi} \\int_0^p (-\\log v)^{-\\xi} dv\\end{array} [REMOVE_ME_2]$$\n\nfor $x \\geq \\mu - \\sigma / \\xi$ if $\\xi > 0$, $x \\leq \\mu - \\sigma / \\xi$ if $\\xi < 0$, $-\\infty < x < \\infty$ if $\\xi = 0$, $0 < p < 1$, $-\\infty < \\mu < \\infty$, the location parameter, $\\sigma > 0$, the scale parameter, and $-\\infty < \\xi < \\infty$, the shape parameter."}],["$","meta","6",{"property":"og:url","content":"https://r-packages.io/packages/VaRES/gev"}],["$","meta","7",{"property":"og:site_name","content":"R PACKAGES"}],["$","meta","8",{"property":"og:locale","content":"en_US"}],["$","meta","9",{"property":"og:image:type","content":"image/png"}],["$","meta","10",{"property":"og:image","content":"https://r-packages.io/packages/VaRES/gev/opengraph-image?6cdc95b0c38aa621"}],["$","meta","11",{"property":"og:image:width","content":"1200"}],["$","meta","12",{"property":"og:image:height","content":"630"}],["$","meta","13",{"property":"og:type","content":"website"}],["$","meta","14",{"name":"twitter:card","content":"summary_large_image"}],["$","meta","15",{"name":"twitter:title","content":"gev() R function from [VaRES]"}],["$","meta","16",{"name":"twitter:description","content":"Computes the pdf, cdf, value at risk and expected shortfall for the generalized extreme value distribution due to Fisher and Tippett (1928) given by [REMOVE_ME]$$ \\begin{array}{ll}&\\displaystylef(x) =\\frac {1}{\\sigma} \\left[ 1 + \\xi \\left( \\frac {x - \\mu}{\\sigma} \\right) \\right]^{-1/\\xi - 1}\\exp \\left\\{ -\\left[ 1 + \\xi \\left( \\frac {x - \\mu}{\\sigma} \\right)\\right]^{-1/\\xi} \\right\\},\\\\&\\displaystyleF(x) = \\exp \\left\\{ -\\left[ 1 + \\xi \\left( \\frac {x - \\mu}{\\sigma} \\right) \\right]^{-1/\\xi} \\right\\},\\\\&\\displaystyle{\\rm VaR}_p (X) = \\mu - \\frac {\\sigma}{\\xi} + \\frac {\\sigma}{\\xi} (-\\log p)^{-\\xi},\\\\&\\displaystyle{\\rm ES}_p (X) = \\mu - \\frac {\\sigma}{\\xi} + \\frac {\\sigma}{p \\xi} \\int_0^p (-\\log v)^{-\\xi} dv\\end{array} [REMOVE_ME_2]$$\n\nfor $x \\geq \\mu - \\sigma / \\xi$ if $\\xi > 0$, $x \\leq \\mu - \\sigma / \\xi$ if $\\xi < 0$, $-\\infty < x < \\infty$ if $\\xi = 0$, $0 < p < 1$, $-\\infty < \\mu < \\infty$, the location parameter, $\\sigma > 0$, the scale parameter, and $-\\infty < \\xi < \\infty$, the shape parameter."}],["$","meta","17",{"name":"twitter:image:type","content":"image/png"}],["$","meta","18",{"name":"twitter:image","content":"https://r-packages.io/packages/VaRES/gev/opengraph-image?6cdc95b0c38aa621"}],["$","meta","19",{"name":"twitter:image:width","content":"1200"}],["$","meta","20",{"name":"twitter:image:height","content":"630"}],["$","link","21",{"rel":"icon","href":"/favicon.ico","type":"image/x-icon","sizes":"16x16"}],["$","meta","22",{"name":"next-size-adjust"}]]

gev function