我有一些关于特定感染流行率的数据，为每个国家/地区提供了 6 个不同年龄组。我正在尝试找到一个合适的分布，它可能适合使用 fitdistrplus 对 prev 进行建模。
流行变量的直方图显示它似乎不是单峰的，但 logit 或 log 转换表明存在一些偏斜。现在，由于起始值或我不知道的某事，我无法找到适合数据的分布。有人可以建议吗？
这是我的数据
prev=c( 0.4 ,0.4 ,0.3333 ,0.2273 ,0.2273 ,0.1818 ,0.0733 ,0.0807 ,0.2 ,0.2 ,0.2 ,0.1053 ,0.2083 ,0.1585 ,0.1017 ,0.1017 ,0.1017 ,0.1059 ,0.3902 ,0.3981 ,0.4103 ,0.4706 ,0.4706 ,0.4655 ,0.037 ,0.0432 ,0.0488 ,0.1538 ,0.1667 ,0.0556 ,0.1277 ,0.101 ,0.0641 ,0.034 ,0.0267 ,0.0463 ,0.0152 ,0.0277 ,0.0268 ,0.0211 ,0.0185 ,0.019 ,0.1818 ,0.2384 ,0.1442 ,0.1481 ,0.1111 ,0.1333 ,0.5018 ,0.2983 ,0.2649 ,0.2649 ,0.2649 ,0.2593 ,0.3442 ,0.2774 ,0.1269 ,0.1269 ,0.1269 ,0.1272 ,0.1708 ,0.136 ,0.048 ,0.048 ,0.048 ,0.0478 ,0.4261 ,0.303 ,0.1891 ,0.1891 ,0.1891 ,0.1891 ,0.12 ,0.0779 ,0.0306 ,0.0476 ,0.1 ,0.0862 ,0.1733 ,0.1386 ,0.0947 ,0.0822 ,0.0392 ,0 ,0.453 ,0.4287 ,0.3898 ,0.3756 ,0.3953 ,0.3776 ,0.3818 ,0.278 ,0.184 ,0.1529 ,0.1077 ,0.0769 ,0.2398 ,0.1421 ,0.1353 ,0.1269 ,0.1158 ,0.1228 ,0.1 ,0.1233 ,0.1162 ,0.1078 ,0.1238 ,0.0532 ,0.2636 ,0.1948 ,0.0767 ,0.0821 ,0.0661 ,0 ,0 ,0.0625 ,0.0635 ,0.0576 ,0.0455 ,0)
prev_log =c(,-0.916290731874155 ,-0.916290731874155 ,-1.09871229366844 ,-1.48148454812364 ,-1.48148454812364 ,-1.70484809723876 ,-2.61319467008953 ,-2.51701670370623 ,-1.6094379124341 ,-1.6094379124341 ,-1.6094379124341 ,-2.25094185984221 ,-1.56877593071521 ,-1.8420006856648 ,-2.28572797592762 ,-2.28572797592762 ,-2.28572797592762 ,-2.24526002637478 ,-0.941095850793126 ,-0.921052048975866 ,-0.890866679533997 ,-0.753746802688875 ,-0.753746802688875 ,-0.764643182265015 ,-3.29683736633791 ,-3.14191478373207 ,-3.02002496612304 ,-1.87210222191059 ,-1.79155948922539 ,-2.8895720777256 ,-2.05807151594364 ,-2.29263476214088 ,-2.74731091505551 ,-3.38139475436598 ,-3.62309171357593 ,-3.07261331788995 ,-4.18645985112991 ,-3.58632286578884 ,-3.61935339146533 ,-3.85848223850012 ,-3.98998454689786 ,-3.9633162998157 ,-1.70484809723876 ,-1.43380534379094 ,-1.93655405413129 ,-1.90986755770838 ,-2.19732458233655 ,-2.01515305179747 ,-0.689553645049815 ,-1.20965558746143 ,-1.32840288270411 ,-1.32840288270411 ,-1.32840288270411 ,-1.34976958643752 ,-1.0665323952047 ,-1.28229477110141 ,-2.0643559042618 ,-2.0643559042618 ,-2.0643559042618 ,-2.06199462807612 ,-1.76726199762767 ,-1.99510039324608 ,-3.03655426807425 ,-3.03655426807425 ,-3.03655426807425 ,-3.04072963948473 ,-0.853081218476271 ,-1.19402247347277 ,-1.66547930331773 ,-1.66547930331773 ,-1.66547930331773 ,-1.66547930331773 ,-2.12026353620009 ,-2.55232932610543 ,-3.4867552700238 ,-3.04492251774476 ,-2.30258509299405 ,-2.45108510131249 ,-1.75273108226058 ,-1.97616319222633 ,-2.3570412787901 ,-2.49859997692 ,-3.23907853218572 , ,-0.791863153499103 ,-0.846997905378206 ,-0.942121491908677 ,-0.979230531648029 ,-0.928110308679497 ,-0.973919844710791 ,-0.96285836769049 ,-1.2801341652915 ,-1.69281952137315 ,-1.87797116604712 ,-2.22840569481979 ,-2.56524940247054 ,-1.42795003638872 ,-1.95122424387908 ,-2.00026074380539 ,-2.0643559042618 ,-2.15589071384324 ,-2.0971982632691 ,-2.30258509299405 ,-2.09313486881184 ,-2.15244243456433 ,-2.22747762050724 ,-2.08908791873164 ,-2.93369688263454 ,-1.33332247635378 ,-1.6357818877737 ,-2.56785357060893 ,-2.49981726252375 ,-2.7165865321245 , , ,-2.77258872223978 ,-2.75671537308349 ,-2.85423271128029 ,-3.09004295302523 )
prev_logit= c(-0.405465108108164 ,-0.405465108108164 ,-0.693297184310321 ,-1.22362014408104 ,-1.22362014408104 ,-1.50419962375192 ,-2.53706927970004 ,-2.43287393559381 ,-1.38629436111989 ,-1.38629436111989 ,-1.38629436111989 ,-2.13967504741362 ,-1.33520318391046 ,-1.66943142031353 ,-2.17847678518065 ,-2.17847678518065 ,-2.17847678518065 ,-2.13332237313391 ,-0.446471606365144 ,-0.413388088547454 ,-0.362725333558318 ,-0.117735813499739 ,-0.117735813499739 ,-0.138219633747978 ,-3.2591354991539 ,-3.0977538879463 ,-2.96999403251747 ,-1.70510268121442 ,-1.60919793163141 ,-2.83236660395482 ,-1.92144963840068 ,-2.18616251763036 ,-2.68106426923659 ,-3.34680330959636 ,-3.59602879402624 ,-3.02520719549268 ,-4.17114314701801 ,-3.55823198562232 ,-3.59218772339256 ,-3.83715645178536 ,-3.97131128163224 ,-3.94413348039892 ,-1.50419962375192 ,-1.16147154828596 ,-1.78083547913187 ,-1.74958142777504 ,-2.07955404660204 ,-1.87209066895564 ,0.00720003110424186 ,-0.85540627073754 ,-1.02065414810202 ,-1.02065414810202 ,-1.02065414810202 ,-1.04960999247462 ,-0.644632980633109 ,-0.957395310832809 ,-1.92865072209642 ,-1.92865072209642 ,-1.92865072209642 ,-1.92594578361284 ,-1.57996809920715 ,-1.848917883068 ,-2.98736402388347 ,-2.98736402388347 ,-2.98736402388347 ,-2.99174945726301 ,-0.297781104608451 ,-0.833052605251155 ,-1.4558687662861 ,-1.4558687662861 ,-1.4558687662861 ,-1.4558687662861 ,-1.99243016469021 ,-2.47122772466839 ,-3.45567731445294 ,-2.99615235337533 ,-2.19722457733622 ,-2.36094155145952 ,-1.56241767553707 ,-1.82696688586421 ,-2.25755238028936 ,-2.4128241998986 ,-3.19908952396936 , ,-0.188556676938947 ,-0.287157092126485 ,-0.448152985209109 ,-0.508266441307169 ,-0.425087496976527 ,-0.499747538592836 ,-0.481915118406369 ,-0.954404025202189 ,-1.48947859735512 ,-1.71203463850249 ,-2.11445281474376 ,-2.48523169448451 ,-1.15377631396173 ,-1.79795650747586 ,-1.85488809078964 ,-1.92865072209642 ,-2.03281871625325 ,-1.96617800083069 ,-2.19722457733622 ,-1.96154444842424 ,-2.02891794827883 ,-2.11341266421927 ,-1.9569270151293 ,-2.87902948129223 ,-1.02734064673057 ,-1.4191173025572 ,-2.48805250040537 ,-2.41415043576666 ,-2.64820061925803 , , ,-2.70805020110221 ,-2.6911096159855 ,-2.79490724519548 ,-3.0434753172089 ,
group= c(1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6 ,1 ,2 ,3 ,4 ,5 ,6)
id= c(950 ,950 ,950 ,950 ,950 ,950 ,979 ,979 ,979 ,979 ,979 ,979 ,982 ,982 ,982 ,982 ,982 ,982 ,1008 ,1008 ,1008 ,1008 ,1008 ,1008 ,1151 ,1151 ,1151 ,1151 ,1151 ,1151 ,1166 ,1166 ,1166 ,1166 ,1166 ,1166 ,1199 ,1199 ,1199 ,1199 ,1199 ,1199 ,1244 ,1244 ,1244 ,1244 ,1244 ,1244 ,1267 ,1267 ,1267 ,1267 ,1267 ,1267 ,1277 ,1277 ,1277 ,1277 ,1277 ,1277 ,1286 ,1286 ,1286 ,1286 ,1286 ,1286 ,1292 ,1292 ,1292 ,1292 ,1292 ,1292 ,1306 ,1306 ,1306 ,1306 ,1306 ,1306 ,1323 ,1323 ,1323 ,1323 ,1323 ,1323 ,1367 ,1367 ,1367 ,1367 ,1367 ,1367 ,1399 ,1399 ,1399 ,1399 ,1399 ,1399 ,1438 ,1438 ,1438 ,1438 ,1438 ,1438 ,1447 ,1447 ,1447 ,1447 ,1447 ,1447 ,1488 ,1488 ,1488 ,1488 ,1488 ,1488 ,1521 ,1521 ,1521 ,1521 ,1521 ,1521)
如果这不起作用，我可以考虑使用样条曲线吗？或者可能是一些 GAM 模型，因为我有研究级别的数据，并且对于每个研究，我都有 6 个组的 prev。
plotdist(mydat$p_exact, histo = TRUE, demp = TRUE, breaks=40)
plotdist(mydat$p_log, histo = TRUE, demp = TRUE, breaks=40)
plotdist(mydat$p_logit, histo = TRUE, demp = TRUE, breaks=40)
fit_w <- fitdist(mydat$prev, "weibull")
fit_g <- fitdist(mydat$prev, "gamma")
fit_b <- fitdist(mydat$prev, "beta")
fit_ln <- fitdist(mydat$prev, "lnorm")
当我尝试一些凝视值或将选项添加lower=c(0,0)到 fitdist 时，我遇到了一些错误the function mle failed to estimate the parameters, with the error code 100