请教各位，我用R对别人论文的损失率数据，用beta 分布拟合，参数估计结果是3.97和3.85，而原文用STATA估计的结果是6.36和5.7。做K-S检验，我的P值是0.01835，而原文的P值是0.3657，说明似乎原文的估计结果更为合理。
不知道问题出在哪里，怎么R估计出来的好像不是最优拟合参数呢？
PS：我用R中其他函数的运行结果也类似。
R程序如下：
res =fitdistr(rate, "beta", start=list(shape1 =4, shape2 =5))
ks.test(rate,"pbeta",3.97,3.85)
ks.test(rate,"pbeta",6.36,5.7)


数据为(附件为csv格式)：
rate
0.599771943 0.511062689 0.577314431 0.466203107 0.576348136 0.540878457 0.543063376 0.56423037 0.516957536 0.616257004 0.647675622 0.539647152 0.582352102 0.569858168 0.658330823 0.378698909 0.627298259 0.584641644 0.718358437 0.659514051 0.563963013 0.545025851 0.576463468 0.747825764 0.352094528 0.382502407 0.589857646 0.769233635 0.540446685 0.505931663 0.478257294 0.469807752 0.569219725 0.736773087 0.291069612 0.395775209 0.3616732 0.407031959 0.354412221 0.566159696 0.195480866 0.638889177 0.459494258 0.537586609 0.514305604 0.536957079 0.501197678 0.60091719 0.506864483 0.469615946 0.673435468 0.618778027 0.451982626 0.516420803 0.631793362 0.537203055 0.034412497 0.555828896 0.46080843 0.57670383 0.632716515 0.564006127 0.353356739 0.571730419 0.703004476 0.43509963 0.425238753 0.807786571 0.744608408 0.592720737 0.443824844 0.511965534 0.415364792 0.485379531 0.395287594 0.299500312 0.274880099 0.476667621 0.230888804 0.548888983 0.213454156 0.604876889 0.526203992 0.527006971 0.530583102 0.486716208 0.451622189 0.510260854 0.397460449 0.757614502 0.537507528 0.524631384 0.622800279 0.561640978 0.630584222 0.642947822 0.583195325 0.569920466 0.759640385 0.64628938 0.606067059 0.844084846 0.447349754 0.54565814 0.57175306 0.527548254 0.482418718 0.807394323 0.444930496 0.239630441 0.207446825 0.182819312 0.770257175 0.787544778 0.358453988 0.282961922 0.335806593 0.481910397 0.199464719 0.501315112 0.243644068 0.622408539 0.668702927 0.533666322 0.59954548 0.559020372 0.478308573 0.723602915 0.55158703 0.462138878 0.601056881 0.572810442 0.262992378 0.71389781 0.521414655 0.457197926 0.508422845 0.760361924 0.455721581 0.739619591 0.816359315 0.620054898 0.850544591 0.496535458 0.567783699 0.671413676 0.576214231 0.548306387 0.737373508 0.547505497 0.186240973 0.075383271 0.027820711 0.340728379 0.271819453 0.322715148 0.265764393 0.313292572 0.219300201 0.489138118 0.417781381