如何利用1-99级数值推导100-1000级对应数值？

需要生成100到1000级的数值，但目前只有1-99级的原始数据。

已尝试的两种推导思路 #

• 第一种（非最优解）：计算相邻等级间的增长比例。例如：
  • 98级到99级的增长比例：1.48549052859962 / 1.47549052855247 = 1.006777407142667666027802785427
  • 97级到98级的增长比例：1.47549052855247 / 1.46549052844927 = 1.006823653861333136524863886226
• 第二种（更接近可行解）：关注相邻等级差值的衰减比例。例如：
  • 99级与98级的差值，除以98级与97级的差值：0.01000000004715/0.0100000001032=0.99999999439500005784359940305405
  • 98级与97级的差值，除以97级与96级的差值：0.0100000001032/0.01000000021209=0.99999998911100023094479610189182

编写的C#代码 #

版本一（含临时变量） #

var rawData = new {startValue = 1.48549052859962, startValueChange = 1.006777407142667666027802785427,
  valueChangeDelta = 0.99999998911100023094479610189182};
int newLevels = 901;
double currentDeltaIncrease=rawData.startValueChange;
double currentValue=rawData.startValue;
for(int i = 1; i <= newLevels; i++) {
  currentDeltaIncrease*=rawData.valueChangeDelta;
  currentValue*=currentDeltaIncrease;
  Console.WriteLine(currentValue);
}

版本二（移除临时变量） #

for(int i = 1; i <= newLevels; i++) {
  Console.WriteLine(rawData.startValue * Math.Pow(rawData.startValueChange * Math.Pow(rawData.valueChangeDelta, i), i));
}

遇到的问题 #

用2级数据反向推导3到99级数值时，结果与原始数据不符，求正确的推导方法。

1-99级原始数值 #

0.0534378655888462
0.103417958130935
0.150187142379338
0.193976721559392
0.235003285878962
0.273469522127392
0.309564985803977
0.343466837176423
0.37534054263011
0.40534054263011
0.433610887579783
0.460285842822386
0.485490463995477
0.509341143911967
0.531946132106459
0.553406028151031
0.573814249810801
0.593257477076532
0.611816073079128
0.629564482859128
0.646571610933278
0.662901178569855
0.678612061654716
0.693758610000949
0.708390948926613
0.722555263897232
0.736294069002583
0.749646460010777
0.762648352716717
0.775332707276717
0.787729739196369
0.799867117614635
0.811770151503618
0.82346196438055
0.834963658106136
0.846294466321637
0.857471898055803
0.868511872012087
0.879428842026456
0.890235914166456
0.900944955923168
0.911566697929096
0.922110828617022
0.932586082217298
0.943000320474056
0.953360608444246
0.963673284727383
0.973944026458308
0.984177909380165
0.994379463300165
1.00455272321654
1.01470127639133
1.02482830563044
1.0349366290194
1.04502873635108
1.05510682246933
1.06517281774116
1.07522841585884
1.0852750991623
1.0953141616623
1.10534672993426
1.11537378204347
1.12539616465293
1.13541460845618
1.14542974206903
1.15544210450583
1.16545215635806
1.17546028978574
1.18546683742443
1.19547208030443
1.20547625487165
1.21547955919368
1.22548215842847
1.23548418962761
1.24548576594038
1.25548698028024
1.26548790850992
1.27548861219737
1.28548914098981
1.29548953464981
1.30548982479273
1.31549003636185
1.3254901888738
1.33549029746387
1.34549037375782
1.35549042659397
1.36549046261702
1.3754904867624
1.385490502648
1.395490512888
1.40549051934176
1.41549052330894
1.4254905256807
1.43549052705509
1.44549052782396
1.45549052823718
1.46549052844927
1.47549052855247
1.48549052859962

内容的提问来源于stack exchange，提问作者koji0285