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J'ai des données qui décrivent la fréquence à laquelle un événement se produit pendant une heure ("nombre par heure", nph) et la durée des événements ("durée en secondes par heure", dph).

Ce sont les données d'origine:

nph <- c(2.50000000003638, 3.78947368414551, 1.51456310682008, 5.84686774940732, 4.58823529414907, 5.59999999993481, 5.06666666666667, 11.6470588233699, 1.99999999998209, NA, 4.46153846149851, 18, 1.05882352939726, 9.21739130425452, 27.8399999994814, 15.3750000002237, NA, 6.00000000004109, 9.71428571436649, 12.4848484848485, 16.5034965037115, 20.6666666666667, 3.49999999997453, 4.65882352938624, 4.74999999996544, 3.99999999994522, 2.8, 14.2285714286188, 11.0000000000915, NA, 2.66666666666667, 3.76470588230138, 4.70588235287673, 13.2727272728677, 2.0000000000137, 18.4444444444444, 17.5555555555556, 14.2222222222222, 2.00000000001663, 4, 8.46153846146269, 19.2000000001788, 13.9024390245481, 13, 3.00000000004366, NA, 7.36000000006855, 1.61137440758472, 1.50000000000873, 3.36585365857481, 22.3750000003256, 10.8387096775008, 2.92307692305075, 3.48837209304214, 5.17647058827074, 37.6666666666667, 1.17647058824335, 7.45454545462435, 36.2352941171508, 6.82352941167125, 2.22222222222222, 6.13333333333333, 11.4285714286665, 42.7058823523563, 28.1052631584975, 18.3333333333333, 1.24999999999091, 5.1034482758211, 1.82857142855926, 1.30693069306629, 3.22222222222222, 17.2800000001609, 10.5714285715165, 7.81818181826456, 3.14285714288328, 4.05194805197256, 3.6, 23.0909090904203, 0.249999999998181, 10, 27.3043478258106, 2.49999999998181, 2.00000000001663, 9.14285714293317, 4.74999999996544, 29.3999999996577, 16.9999999998021, 15.7777777777778, 1.74999999998727, 3.46666666666667, 2.45161290324422, 2.05231388331614, 2.60000000001513, 15.4054054053569, 4, 12.2222222222222, 2.46153846151642, 8.15384615399219, 2.23529411761644, 15.1111111111111, 0.23529411764867, 10.5454545455661, 17.5714285715747, 2.3030303030303, 1.37931034481651, 8.32000000007749, 5.1578947368105, 24.1999999997183, 15.4782608694085, 21.8749999998408, 2.74999999997999, 9.91304347823578, 3.86206896548623, 1.16959064328441, 2.84210526319272, 12.857142856929, 4, 3.69230769227463, 2, NA, 1.88888888888889, 15.4285714283148, 0.222222222222222, 6.16666666666667, 13.1034482757569, 3.19999999996275, 4.87499999996453, 2.88000000002682, 5.12499999996271, 26.6666666666667, 9.75000000014188, 17.2048192770602, 1.99999999998545, 1.65517241377981, 3.16666666666667, 2.23529411766237, 6.82352941181143, 2.74999999991996, 2.99999999997817, 11.4929577463281, 1.59999999998137, 8.65116279074452, 5.69230769240964, 13.7777777777778, 0.222222222222222, 10.6000000002468, 13.91304347812, 2.75862068963302, NA, 4.26666666666667, 5.64705882356808, 2.74999999997999, 15.047619047619, 16.6666666666667, 1.49999999998909, 4.62499999996635, 5.71428571428571, 1.83206106868927, 2.44444444444444, 2.4, 3.9999999999709, 2.33333333333333, 3.20000000007451, 5.931034482711, 7.14285714273835, 14.7272727274286, 0.352941176465754, 8.40000000019558, 10.1250000001473, 2.66666666666667, NA, 2.66666666666667, 4.7058823529734, 4.83333333333333, 9.31034482751146, 24.5882352937809, 2.13333333333333, 10.1739130434525, 5.56521739124801, 2.12658227848728, 1.88888888888889, 5.80000000013504, 7.14285714291654, 1.71428571429997, 1.99999999994179, NA, 5.00000000007276, NA, 0.129032258062578, 8.22222222222222, 7.16666666666667, 4.13793103444954, 2.82352941178404, 3.07692307697818, 4.00000000004902, 4.74999999986176, 9.75000000014188, 20.1333333333333, 2.66666666666667, 6.78947368416893, 1.46666666666667, 1.73195876289076, 4.76923076931619, 2.88888888888889, 7.4285714286332, 5.2, 3.384615384676, 4.7727272727399, 6.59999999992317, 11.4545454546667, 1.41176470586302, 11.1999999998696, 6.08000000005662, 4, 4.71428571432492, 5.00000000004158, 6.8, 6.83870967747072, 14.2500000002074, 5.49999999983993, 2.4, 4.71910112354612, 4, 1.72185430463842, 2.44444444444444, 4.30769230776946, 6.30769230780528, 3.53846153852491, 4.35294117641097, NA, 5.99999999990022, NA, NA, 7.42857142857143, 10.1333333333333, 6.79999999992084, 5.54838709681587, 1.83333333333333, 7.06666666666667, 2.9090909091217, 10.8000000001006, NA, 2.13333333333333, NA, 5.09090909090909, 4.21052631570563, 4.00000000003326, 4.28571428571429, 4.28571428574992, 2.49999999998181, 2.76923076928037, 4.99999999985448, 3.87500000005639, NA, NA, 12.2105263159391, 5.44444444444444, 2.6249999999809, 3.74193548389907, 3.28571428574161, 4.88888888888889, 9.33333333333333, 4.21621621620295, NA, 0.8, 4.5306122448549, 4.14285714289159, 3.1137724550985, 0.266666666666667, 5.27272727261567, 1.84615384613731, 8.36363636372488, 2.42857142853104, NA, 2.42857142853104, 8.28571428578318, 1.64705882350685, 8.2, 6.88888888888889, 1.74999999998727, 7.6, 3.33333333333333, 6.24999999995453, 9.56521739120752, 4.93333333333333, 16.4, 2.53333333333333, 7.2, 1.33333333333333, 3.3962264151018, 2, 9.38461538453135, 1.57142857144164, 3.45454545458201, 5.37499999996089, 7.74193548375467, 3.38461538458508, 7, NA, 4.54545454545455, 14.5, 1.93939393939394, 4.33333333333333, 4, 6.58823529402741, 2.90909090902933, 3.32530120480995, 25.6666666666667, 2, 6.54545454545455, 4.4, 3.54378818739119, 1.62499999998818, 4.22222222222222, 2.53333333333333, 14.6666666666667, 2.96296296296296, NA, 3.00000000004366, 16.1999999998114, 1.55555555555556, 3.11111111111111, NA, 4.8, 3.99999999997339, 4, 6.37499999995362, 2.7999999999674, NA, 32.8, 2.49999999998181, 11.0561797754255, NA, 2.75229357793903, 1.7142857142572, 7.66666666666667, 7.28571428577487, 2.36363636358633, 2.14285714287496, 6.27272727274387, 3.62499999997362, 19.6666666666667, 1.71428571427431, 6.60869565210701, 5.57894736838687, 5.84615384610149, 3.03030303030303, 1.33333333333333, 4.87499999996453, 4.71428571432492, 4.74418604653732, 13.0588235292329, 3.12500000004547, NA, 3.37500000004911, 2.41525423729648, 2.37499999998272, 4.54545454550265, 6.28571428576655, 2.55555555555556, 3.17647058819179, 5.59999999993481, 5.85714285719156, 7.42857142844789, NA, 4.83333333333333, 5.33333333333333, 4.48484848484848, 2.93333333333333, 3.83333333333333, 5.52941176474375, 9.33333333333333, 5.16666666666667, 18, 2.82352941178404, 5.54838709681587, 3.55555555555556, 1.25237191650965, 2, 2.16666666666667, 7.16666666666667, 3.00000000002495, 2.83333333333333, 2.48275862068966, 4.42857142860825, 11.1428571426718, NA, 5.52380952380952, 34.3448275859312, 4.75000000006912, 3.26315789471685, 10.2857142857998, 10.5555555555556, 5.00000000004158, 19.0843373493441, 20.6153846152, 2.24999999998363, 8.59259259259259, 4.25806451616101, 2.85714285716014, 5.1578947368105, 8.66666666666667, 3.14285714280487, 6.30769230763582, 6.79999999992084, 8.07692307663376, 5.73333333333333, 8.46153846146269, 2.34482758618807, 4.31999999991953, 4.57142857135254, 2.87500000004184, 2.28571428567627, 0.857142857149985, 10.2352941175069, 3.26086956520914, NA, 13.3333333333333, 2.75000000004002, 6.45161290312889, 3.61290322575218, 1.48854961831995, 3.37499999997544, 4.0540540540413, 5.73333333333333, 3.85714285707871, 3, 6.31578947364551, 1.55555555555556, 7.84615384608358, 0.4, 7.66666666666667, NA, 7.85185185185185, 2.59090909091595, 7.28571428577487, 5.74999999995816, 3.28571428574161, 16.043478260829, 15.8000000003679, 2.50000000003638, NA, 2.06451612904776, 1.82163187855948, 0.874999999993634, 13.2000000001229, 6.92307692301493, 3.7142857143166, 3.00000000001343, 5.83333333333333, 3.86666666666667, 9.39999999989057, 2.49999999998181, 6.24000000005811, 4.58823529414907, 3.72413793109428, 3.21428571427235, 6.85714285719988, 8.42857142864151, 5.23076923086291, 10.5454545455661, 14.1428571429747, 4.00000000005821, 4.08791208795393, 8.47058823517811, 3.94422310755509, 3.62500000005275, 6.0000000001397, 1.33333333333333, 3.73333333333333, 6.31578947352942, NA, 4.53333333333333, 8.46153846169001, 0.470588235287673, 2.28571428571429, 22.7142857144746, 8.00000000012846, 2.8108108108285, 4.57142857146658, 5.87500000008549, 6.42857142862488, 19.2258064513241, 13.4666666666667, 3.46666666666667, 4.90322580648844, 3.51515151515152, 1.56862745098755, 1.53846153844776, 3.63636363636364, 4.71428571432492, 3.06666666666667, 4.61538461546728, NA, 2.83333333333333, 5.53846153841194, 1.80645161287609, 9.14285714285714, 2.42857142853104, 3.2, 5.00000000007276, 4.42857142860825, 6.12500000008913, 3.24999999990541, 4.16326530608288, 14.6666666666667, 5.37499999996089, 7.43478260867684, 9.93548387104236, 3.73205741626378, 2.24999999998363, 13.7777777777778, 4.74074074074074, 7.4285714286332, 3.61904761904762, 7.13513513511269, 5.28571428575824, 5, 2.5882352940822, 11.5000000001673, 27.1249999998026, 2.875, 2.81081081077544, 9.42857142864983, 7.05882352931509, 3.83333333333333, 16.8695652172205, 16.7692307690806, 10.1333333333333, 5.45454545455989, 7.8750000001146, 1.6883116883219, 2.66666666666667, 11.7857142856653, 3.33333333333333, 6.33333333333333, 7.39999999991385, 12.5882352942039, 4.00000000003326, 6.72727272734392, 3.03030303030303, 6, 30.6666666666667, 3.74999999997272, 3.00000000003011, 8.00000000006652, 8.00000000006009, 2.57142857144995, 10.695652173886, 14.2666666666667, 7.75000000011278, 2.51162790697674, 6.33333333333333, 3.28125000004775, 1.88888888888889, 10.4000000002421, 4.87499999996453, 13.7142857143998, 8.5, NA, 4.87499999996453, 8.181818181645, 1.24999999999091, 4.38095238095238, 27.1764705878631, 2.37499999998272, 2.94117647060838, 11.7142857143831, 5.99999999996324, 2.37499999998272, 14.7637795275455, 14.313253012008)
dph <- c(3.12500000004547, 6.69473684199041, 4.3106796117187, 11.6937354988146, 103.882352941888, 10.9999999998719, 7.33333333333333, 20.3529411761918, 5.23076923072239, NA, 4.61538461534328, 47.5555555555556, 2.94117647054795, 18.9565217389385, 44.3199999991745, 28.5000000004147, NA, 10.4705882353658, 19.000000000158, 25.8181818181818, 43.2167832173461, 51.5555555555556, 8.37499999993906, 6.91764705878563, 9.37499999993179, 5.64705882345207, 4.53333333333333, 27.4285714286627, 14.4285714286914, NA, 1.6, 5.76470588227399, 4.70588235287673, 55.2727272733122, 2.11764705883803, 30.8888888888889, 41.2222222222222, 23.4444444444444, 2.42857142859162, 6.2, 17.0769230767702, 21.2800000001982, 40.8292682931466, 14.5, 6.25000000009095, NA, 15.0400000001401, 5.68720379147547, 2.40000000001397, NA, 26.3750000003838, 18.0645161291679, 3.99999999996418, 6.13953488375417, 8.47058823535212, 128.666666666667, 2.23529411766237, 34.1818181821799, 115.999999998411, 5.99999999991782, 5.77777777777778, 10.6666666666667, 15.4285714286997, 54.8235294110138, 81.315789475428, 42.3333333333333, 1.74999999998727, 7.99999999993577, 4.34285714282825, 1.90099009900552, 5.22222222222222, 39.840000000371, 25.1428571430662, 7.81818181826456, 8.57142857149985, 15.2727272728196, 6.4, 93.0909090889387, 0.374999999997272, 23.1666666666667, 29.3913043475286, 0.874999999993634, 1.71428571429997, 13.5714285715414, 5.49999999995998, 134.799999998431, 77.7999999990943, 18, 2.24999999998363, 5.73333333333333, 3.09677419357165, 2.29376257547098, 5.70000000003318, 23.1891891891162, 14, 13.5555555555556, 1.69230769229254, 9.23076923093455, 4.35294117641097, 48.6666666666667, 0.352941176473005, 16.0000000001693, 56.7142857147573, 1.81818181818182, 1.37931034481651, 19.6800000001833, 6.63157894732779, 134.999999998428, 41.0434782604541, 26.8749999998045, 3.62499999997362, 16.5652173912624, 10.3448275861238, 1.28654970761285, 2.94736842108875, 13.4285714283481, 7.6, 3.2307692307403, 2, NA, 3.44444444444444, 93.1428571413081, 0.111111111111111, 13.6666666666667, 28.1379310342568, 2.39999999997206, 7.8749999999427, 4.00000000003725, 6.99999999994907, 60, 26.8750000003911, 30.5060240963, 3.12499999997726, 3.17241379307798, 4.83333333333333, 9.29411764712247, 12.7058823530282, 4.24999999987631, 6.99999999994907, 9.97183098578469, 2.39999999997206, 8.93023255818789, 15.3846153848909, 94, 0.111111111111111, 21.4000000004983, 29.9130434779581, 1.24137931033486, NA, 15.8666666666667, 7.17647058828444, 1.49999999998909, 37.9047619047619, 27.6666666666667, 1.74999999998727, 9.37499999993179, 17.3333333333333, 11.603053435032, 5.33333333333333, 2.8, 7.99999999994179, 3.5, 1.60000000003725, 7.31034482752751, 6.42857142846452, 56.7272727278731, 0, 21.6000000005029, 28.8750000004202, 1.6, NA, 4.5, 5.64705882356808, 7.16666666666667, 36.2068965514334, 40.235294117096, 4.8, 22.3043478260305, 8.86956521730152, 3.94936708861923, 3.33333333333333, 12.6000000002934, 20.0000000001663, 1.28571428572498, 0.749999999978172, NA, 6.25000000009095, NA, 0.258064516125156, 18.6666666666667, 17, 5.51724137926605, 2.58823529413537, 11.0769230771215, 5.26315789480134, 11.4999999996653, 34.1250000004966, 42.4, 6.53333333333333, 33.1578947366389, 4.4, 4.9484536082593, 11.2307692309704, 5.11111111111111, 23.8571428573412, 0.4, 2.30769230773364, 6.81818181819986, 8.19999999990454, 26.7272727275556, 0.352941176465754, 24.1999999997183, 7.04000000006557, 2.5, 7.14285714291654, 11.4285714286665, 12.1333333333333, 2.83870967744068, 42.7500000006221, 4.99999999985448, 3.33333333333333, 10.112359550456, 16.8, 4.23841059603303, 2.22222222222222, 14.4615384617975, 15.6923076925887, 3.23076923082709, 1.05882352939726, NA, 7.42857142844789, NA, NA, 16.952380952381, 12.4, 6.29999999992666, 85.4193548393512, 4.33333333333333, 11.8666666666667, 6.0000000000635, 19.6800000001833, NA, 3.46666666666667, NA, 13.0909090909091, 12.6315789471169, 5.14285714289991, 9.14285714285714, 12.1428571429581, 2.87499999997908, 1.692307692338, 10.2499999997017, 5.00000000007276, NA, NA, 19.578947368661, 10.4444444444444, 1.74999999998727, 4.77419354842295, 8.57142857149985, 9.66666666666667, 13.5238095238095, 7.29729729727434, NA, 1.6, 9.18367346930048, 6.85714285719988, 4.5508982036055, 0.666666666666667, 10.90909090886, 2.61538461536119, 6.1818181818836, 1.57142857140244, NA, 1.99999999996674, 24.4285714287746, 0.941176470575345, 16.6, 17.6666666666667, 0.999999999992724, 10.2666666666667, 7.5, 11.2499999999181, 11.9999999998785, 12.8, 29.7333333333333, 5.33333333333333, 13.6, 1.84615384615385, 12.7924528302168, 2.4, 23.6923076920955, 2.42857142859162, 4.90909090914286, 3.62499999997362, 11.4193548385381, 4.92307692303284, 17, NA, 16.9090909090909, 20.8333333333333, 0.96969696969697, 8, 11.8333333333333, 10.2352941175069, 5.81818181805867, 6.07228915660947, 39.3333333333333, 4.13333333333333, 9.6969696969697, 11.2, 7.94297352346302, 2.12499999998454, 4.66666666666667, 2.66666666666667, 11.3333333333333, 3.7037037037037, NA, 2.87500000004184, 24.3999999997159, 1.88888888888889, 10.4444444444444, NA, 3.73333333333333, 7.08571428566715, 15.8333333333333, 11.2499999999181, 2.59999999996973, NA, 43.6, 3.24999999997635, 22.9213483149066, NA, 5.22935779808415, 1.85714285711197, 14.3333333333333, 15.4285714286997, 4.363636363544, 1.8571428571583, 7.36363636365585, 6.37499999995362, 51.3333333333333, 3.42857142854862, 1.043478260859, 4.94736842102232, 2.76923076920597, 5.09090909090909, 2.5, 7.49999999994543, 9.71428571436649, 7.25581395352766, 29.8823529407672, 6.62500000009641, NA, 6.12500000008913, 5.59322033900236, 5.12499999996271, 5.45454545460318, 7.00000000005821, 2.44444444444444, 3.05882352936987, 16.9999999998021, 7.71428571434986, 16.8571428568625, NA, 8.83333333333333, 6.77777777777778, 2.78787878787879, 5.06666666666667, 8.83333333333333, 9.17647058829813, 14.1666666666667, 5.5, 36.6666666666667, 4.23529411767606, 7.48387096779814, 5.33333333333333, 2.73244781783923, 2.13333333333333, 2.5, 11.5, 6.42857142862488, 3, 1.79310344827586, 8.00000000006652, 24.8571428567295, NA, 6.09523809523809, 68.5517241373807, 21.2500000003092, 6.21052631575142, 19.2857142858747, 15.1111111111111, 5.5714285714749, 42.6506024095189, 42.615384615003, 4.87499999996453, 13.3333333333333, 11.8709677420246, 8.83116883122224, 6.31578947364551, 9.83333333333333, 1.99999999996674, 7.69230769223881, 4.39999999994878, 17.3076923070723, 8.13333333333333, 16.461538461391, 1.65517241377981, 7.03999999986887, 10.2857142855432, 2.12500000003092, 1.14285714283814, 1.14285714286665, 13.1764705880548, 3.7826086956426, NA, 28.1333333333333, 3.75000000005457, 8.38709677406756, 6.83870967731663, 3.20610687022758, 6.49999999995271, 6.32432432430443, 13.8666666666667, 8.42857142843125, 2.83333333333333, 13.4210526314967, 3.33333333333333, 14.1538461537194, 0.933333333333333, 15.8333333333333, NA, 8.2962962962963, 5.31818181819589, 13.5714285715414, 10.1249999999263, 6.28571428576655, 39.260869565118, 26.6000000006193, 4.00000000005821, NA, 3.74193548389907, 5.35104364326849, 0.749999999994543, 12.0000000001118, 4.30769230765373, 6.57142857148322, 6.00000000002686, 13.3333333333333, 5.33333333333333, 16.1999999998114, 1.87499999998636, 13.1200000001222, 11.0588235294875, 2.0689655172746, 5.57142857140541, 17.1428571429997, 12.8571428572498, 10.4615384617258, 27.2727272730159, 25.5714285716412, 9.25000000013461, 12.3956043957313, 20.8235294114795, 4.54183266930586, 6.25000000009095, 14.000000000326, 1.33333333333333, 8.13333333333333, 7.15789473666668, NA, 62.6666666666667, 18.0000000003224, 0.117647058821918, 6.66666666666667, 43.8571428575075, 8.55172413806835, 5.40540540543942, 7.71428571434986, 11.0000000001601, 18.2857142858663, 52.6451612895318, 26.4, 5.6, 13.1612903226795, 5.93939393939394, 2.48366013073029, 1.53846153844776, 2.36363636363636, 4.14285714289159, 1.33333333333333, 9.23076923093455, NA, 2.83333333333333, 10.9230769229791, 2.19354838706382, 18.6666666666667, 3.57142857136918, 1.6, 8.50000000012369, 9.85714285722482, 11.2500000001637, 1.74999999994907, 6.367346938715, 33, 10.8749999999209, 23.9999999999393, 23.4838709679183, 3.73205741626378, 2.74999999997999, 20.6666666666667, 4.14814814814815, 13.2857142858248, 4.57142857142857, 15.2432432431953, 5.85714285719156, 10, 2.5882352940822, 20.5000000002983, 58.3749999995753, 1.875, 5.08108108101713, 13.5714285715414, 10.8235294116165, 2.66666666666667, 27.4782608692871, 30.9230769228, 17.6, 7.77272727274784, 15.7500000002292, 2.46753246754739, 2.77777777777778, 12.6428571428046, 3.6, 11.2222222222222, 6.79999999992084, 20.705882353083, 2.85714285716662, 14.1818181819683, 3.51515151515152, 11.7777777777778, 57.8888888888889, 3.9999999999709, 5.58620689660779, 15.4285714286997, 11.3548387097627, 1.00000000000832, 23.9999999999393, 25.3333333333333, 20.1250000002929, 4.88372093023256, 13.1111111111111, 2.57812500003752, 2.66666666666667, 12.0000000002794, 7.74999999994361, 23.2857142859079, 10.3333333333333, NA, 4.74999999996544, 12.545454545189, 1.74999999998727, 8, 55.999999999233, 2.12499999998454, 5.05882352944641, 24.5714285716329, 8.21052631573917, 1.99999999998545, 29.17322834643, 30.5060240963)
par(mfrow = c(2, 2))
hist(nph)
hist(dph)
qqnorm(nph)
qqline(nph)
qqnorm(dph)
qqline(dph)

Ce sont les distributions:

Comme les données ne sont évidemment pas distribuées normalement, de nombreux tests statistiques ne peuvent pas être appliqués à ces données. Mais peut-être que je peux transformer les données en une distribution normale?

Comment savoir de quelle distribution il s'agit?
Et comment puis-je transférer les données vers une distribution normale?

Le but est de faire une analyse de la variance (MANOVA) ou d'une telle analyse (les données présentées ici sont les deux variables dépendantes).

Les données semblent avoir une distribution exponentielle . Pour la transformation, un simple journal semble fonctionner correctement.

hist(log(dph), freq=FALSE, ylim=c(0, .4))
lines(seq(-6, 6, by=0.01), dnorm(seq(-6, 6, by=0.01), 2, 1), col="red")
qqnorm(log(dph), ylim=c(0, 5))
qqline(log(dph), col="red")

Toute distribution continue peut être transformée en une distribution normale grâce à un processus appelé gaussianisation (Chen et Gopinath, 2001) . Pour les distributions univariées, la gaussianisation est simple. Si une variable aléatoire a une fonction de distribution cumulative (CDF) et est le CDF d'une normale standard, alors$Y$$F_Y$$\Phi$

aura une distribution normale standard. Ceci est facile à voir, car le CDF de est$X$

Si est distribué de façon exponentielle avec rate , alors les données pourraient être transformées via$Y$$\lambda$

qui ressemble à un logarithme:

Je n'utilise pas R , mais je suis sûr que vous pouvez trouver des implémentations du CDF inverse (également connu sous le nom de fonction quantile ) de la normale, .$\Phi^{-1}$

1. Comment savoir de quelle distribution il s'agit? Ici, vous pouvez utiliser certains tests statistiques du package R fitdistrplus. Dans le package, vous trouverez des cratères adaptées, c'est-à-dire AIC, BIC, etc. Voici les méthodes.

   • ESTIMATION DE VRAISEMBLANCE MAXIMALE
   • ESTIMATION DE L'APPARIEMENT DES MOMENTS
   • ESTIMATION DE CORRESPONDANCE QUANTILE
   • ESTIMATION MAXIMALE DE LA BONNE ADAPTATION (Statistiques de qualité de l'ajustement et critères de qualité de l'ajustement)

Enfin, vous trouverez parmi plusieurs modèles théoriques le meilleur qui ressemble à vos données observées.

2. Et comment puis-je transférer les données vers une distribution normale? Ici, vous pouvez utiliser Box Cox Transfom

   Box_Cox_tran=function(x, lambda, jacobian.adjusted = FALSE) 
   {
     bc1 <- function(x, lambda) 
     {
       if (any(x[!is.na(x)] <= 0)) 
         stop("First argument must be strictly positive.")
       z <- if (abs(lambda) <= 1e-06) 
         log(x)
       else ((x^lambda) - 1)/lambda
       if (jacobian.adjusted == TRUE) {
         z * (exp(mean(log(x), na.rm = TRUE)))^(1 - lambda)
       }
       else z
     }
     out <- x
     out <- if (is.matrix(out) | is.data.frame(out)) {
       if (is.null(colnames(out))) 
         colnames(out) <- paste("Z", 1:dim(out)[2], sep = "")
       for (j in 1:ncol(out)) {
         out[, j] <- bc1(out[, j], lambda[j])
       }
       colnames(out) <- paste(colnames(out), round(lambda, 2), 
                              sep = "^")
       out
     }
     else bc1(out, lambda)
     out
   }
   

Voici mon exmaple de travail:

# ---------------------------------------------------------------------------------------------------------------------------
# Objective three starts Here
# (3)= Bivariate modelling of annual maxima using traditional approach 
# a)    First transform onbserved seasonal maxima into normal distribution using Box-Cox Transformations(x to z)
# b)    Finaly, Estimate Pearson coefficient using traditional bivariate normal distribution
# ---------------------------------------------------------------------------------------------------------------------------
rm(list=ls())
Sys.setenv(LANGUAGE="en")  # to set languege from Polish to English
setwd("C:/Users/sdebele/Desktop/From_oldcomp/Old_Computer/Seasonal_APP/Data/Data_Winter&Summer")
# Loading the required package here
library(MASS)
library(geoR)
require(scales)
require(plyr)
require(car)
library(ggplot2)
require(alr3)
library(ggplot2)
library(reshape2)
library(nortest)
require(AID)
require(distr)
require(fBasics)
# -----------------------------------------------------------------------------------------------------------------------------
# Here the Box-Cox Transformations equations
# x(lambda)=x^lamda-1/lambda, if lambda is not zero
# else log(x) if lambda=0
#--------------------------------------------------------------------------------------------------------------------------------
# Here is the data for six guaging stations of dependant ( 51.12% to 89.85%)
filenames=c("ZAPALOW.txt","GORLICZYNA.txt","SARZYNA.txt","OSUCHY.txt","HARASIUKI.txt","RUDJASTKOWSKA.txt")
# ---------------------------------------------------------------------------------------------------------------------------
# (1)= For ZAPALOW hydrological guaging stations starts here
# --------------------------------------------------------------------------------------------------------------------------------
ZAPALOW=read.table(file=filenames[1],head=T,sep="\t")
newZAPALOW <- na.omit(ZAPALOW) # to eliminte the missing value from the data sets 
Years=newZAPALOW$Year
    Winter=newZAPALOW$Winter
Summer=newZAPALOW$Sumer
    source("Box_Cox_Transfom.R") # R_script containing the tranformation equations 
    # estimation of lambda using AID R package 
    # boxcoxnc(Sumer, method="ac", lam=seq(-2,2,0.01), plotit=TRUE, rep=30, p.method="BY")
    # boxcoxnc(Winter, method="ac", lam=seq(-2,2,0.01), plotit=TRUE, rep=30, p.method="BY")
    Trans_Win=boxcoxnc(Winter)
    Trans_Sum=boxcoxnc(Summer)
    Winter_trans=Box_Cox_tran(Winter,Trans_Win$result[1,1],jacobian.adjusted=T)
Summer_trans=Box_Cox_tran(Summer,Trans_Sum$result[1,1],jacobian.adjusted=T)
    newZAPALOW[,4]=Winter_trans
    newZAPALOW[,5]=Summer_trans
    colnames(newZAPALOW)= c("Year","Winter " ,"Summer","Winter_Trans","Summer_Trans")
    par(mfrow=c(2,2))
    par("lwd"=2)
    ## Plot histogram with overlayed normal distribution.
    hist(newZAPALOW[,4],main="",xlab="Discharge",freq=FALSE,col="lightblue")
    curve(dnorm(x,mean=mean(newZAPALOW[,4]),sd=sd(newZAPALOW[,4])), add=TRUE, col="darkred",lwd=2)
    qq.plot(newZAPALOW[,4], dist= "norm", col=palette()[1], ylab="Sample Quantiles",
            main="Normal Probability Plot", pch=19)
    #b <- mydata[,c(2,3)] # select interesting columns
    result <- shapiro.test(newZAPALOW[,4]) # checking for normality test 
    result$p.value
ad.test(newZAPALOW[,4]) # checking for normality test 
## Plot histogram with overlayed normal distribution.
hist(newZAPALOW[,5],main="",xlab="Discharge",freq=FALSE,col="lightblue")
curve(dnorm(x,mean=mean(newZAPALOW[,5]),sd=sd(newZAPALOW[,5])), add=TRUE, col="darkred",lwd=2)
qq.plot(newZAPALOW[,5], dist= "norm", col=palette()[1], ylab="Sample Quantiles",
        main="Normal Probability Plot", pch=19)
result <- shapiro.test(newZAPALOW[,5]) # checking for normality test 
result$p.value
ad.test(newZAPALOW[,5]) # checking for normality test 
write.table(newZAPALOW, "newZAPALOW_trans.txt", sep="\t")
For sure this will be helpfull for you.