椭圆由方程Ax^2+Bxy+Cy^2+Dx+Ey+F=0表示，其中A、B、C、D、E、F为拟合参数，x、y为变量。现在有一系列的{x,y}数据，想要拟合得到A~F的参数值。但是给出的拟合结果是A~F六个参数全部为0，当然这是可以理解的，因为六个参数全部为0时，等式确实成立。想请教如何能够避免该问题，得到非0的参数值。非常感谢！！！
数据点做图如附图所示，其中100个数据点分别为：{{0.42867, 0.29316}, {0.47231, 0.52341}, {0.48339, 0.4966}, {0.34955, 0.2727}, {0.48025, 0.34219}, {0.24471, 0.43896}, {0.25033, 0.48827}, {0.40938, 0.28984}, {0.49642, 0.45106}, {0.43251, 0.55954}, {0.34588, 0.5664}, {0.27422, 0.32186}, {0.2725, 0.35105}, {0.47521, 0.33895}, {0.41837, 0.55882}, {0.35466, 0.57093}, {0.4879, 0.49352}, {0.40899, 0.29149}, {0.25589, 0.33504}, {0.2597, 0.35743}, {0.43128, 0.29059}, {0.27037, 0.47792}, {0.40481, 0.274}, {0.25079, 0.43302}, {0.25335, 0.35232}, {0.38475, 0.57225}, {0.39276, 0.28701}, {0.49691, 0.39056}, {0.39209, 0.27929}, {0.4263, 0.5599}, {0.42127, 0.27557}, {0.28463, 0.51501}, {0.49577, 0.42361}, {0.29729, 0.30011}, {0.49573, 0.47756}, {0.47646, 0.51795}, {0.32093, 0.5567}, {0.43953, 0.55303}, {0.47472, 0.50352}, {0.45833, 0.30911}, {0.25645, 0.43254}, {0.28422, 0.51962}, {0.2634, 0.51431}, {0.49901, 0.4231}, {0.23357, 0.44264}, {0.48326, 0.35592}, {0.23996, 0.44389}, {0.29704, 0.53519}, {0.28227, 0.51102}, {0.27067, 0.49698}, {0.33554, 0.27347}, {0.41947, 0.56016}, {0.23213, 0.41705}, {0.25502, 0.3416}, {0.29413, 0.5491}, {0.37912, 0.27493}, {0.25152, 0.45521}, {0.30816, 0.28566}, {0.29243, 0.30207}, {0.38722, 0.573}, {0.32901, 0.28196}, {0.47873, 0.50726}, {0.23531, 0.44914}, {0.2353, 0.40606}, {0.49352, 0.46001}, {0.38458, 0.56985}, {0.47637, 0.5083}, {0.35976, 0.26933}, {0.40485, 0.56567}, {0.49548, 0.38141}, {0.41039, 0.29039}, {0.42901, 0.30339}, {0.45509, 0.31613}, {0.24907, 0.39946}, {0.25489, 0.43712}, {0.3154, 0.28807}, {0.42415, 0.28183}, {0.24795, 0.39934}, {0.3441, 0.27762}, {0.44443, 0.54751}, {0.36023, 0.57168}, {0.36901, 0.58005}, {0.34992, 0.56988}, {0.44218, 0.54659}, {0.32205, 0.28402}, {0.38432, 0.27235}, {0.26589, 0.3527}, {0.4038, 0.28042}, {0.36034, 0.56435}, {0.46004, 0.32954}, {0.47672, 0.51373}, {0.42796, 0.5588}, {0.49415, 0.46632}, {0.29093, 0.30224}, {0.4193, 0.27234}, {0.39982, 0.27218}, {0.27294, 0.50896}, {0.35982, 0.27621}, {0.342, 0.28235}, {0.39972, 0.28645}}

码嘞？

dataraw={{0.42867,0.29316},{0.47231,0.52341},{0.48339,0.4966},{0.34955,0.2727},{0.48025,0.34219},{0.24471,0.43896},{0.25033,0.48827},{0.40938,0.28984},{0.49642,0.45106},{0.43251,0.55954},{0.34588,0.5664},{0.27422,0.32186},{0.2725,0.35105},{0.47521,0.33895},{0.41837,0.55882},{0.35466,0.57093},{0.4879,0.49352},{0.40899,0.29149},{0.25589,0.33504},{0.2597,0.35743},{0.43128,0.29059},{0.27037,0.47792},{0.40481,0.274},{0.25079,0.43302},{0.25335,0.35232},{0.38475,0.57225},{0.39276,0.28701},{0.49691,0.39056},{0.39209,0.27929},{0.4263,0.5599},{0.42127,0.27557},{0.28463,0.51501},{0.49577,0.42361},{0.29729,0.30011},{0.49573,0.47756},{0.47646,0.51795},{0.32093,0.5567},{0.43953,0.55303},{0.47472,0.50352},{0.45833,0.30911},{0.25645,0.43254},{0.28422,0.51962},{0.2634,0.51431},{0.49901,0.4231},{0.23357,0.44264},{0.48326,0.35592},{0.23996,0.44389},{0.29704,0.53519},{0.28227,0.51102},{0.27067,0.49698},{0.33554,0.27347},{0.41947,0.56016},{0.23213,0.41705},{0.25502,0.3416},{0.29413,0.5491},{0.37912,0.27493},{0.25152,0.45521},{0.30816,0.28566},{0.29243,0.30207},{0.38722,0.573},{0.32901,0.28196},{0.47873,0.50726},{0.23531,0.44914},{0.2353,0.40606},{0.49352,0.46001},{0.38458,0.56985},{0.47637,0.5083},{0.35976,0.26933},{0.40485,0.56567},{0.49548,0.38141},{0.41039,0.29039},{0.42901,0.30339},{0.45509,0.31613},{0.24907,0.39946},{0.25489,0.43712},{0.3154,0.28807},{0.42415,0.28183},{0.24795,0.39934},{0.3441,0.27762},{0.44443,0.54751},{0.36023,0.57168},{0.36901,0.58005},{0.34992,0.56988},{0.44218,0.54659},{0.32205,0.28402},{0.38432,0.27235},{0.26589,0.3527},{0.4038,0.28042},{0.36034,0.56435},{0.46004,0.32954},{0.47672,0.51373},{0.42796,0.5588},{0.49415,0.46632},{0.29093,0.30224},{0.4193,0.27234},{0.39982,0.27218},{0.27294,0.50896},{0.35982,0.27621},{0.342,0.28235},{0.39972,0.28645}};
datanumber=Length[dataraw];
data=Table[0,{datanumber},{3}];
Do[data[[i,1]]=dataraw[[i,1]];
data[[i,2]]=dataraw[[i,2]];
data[[i,3]]=0;
,{i,1,datanumber}];
a=.;
b=.;
c=.;
d=.;
e=.;
f=.;
xyfit=NonlinearModelFit[data,a*x^2+b*x*y+c*y^2+d*x+e*y+f,{a,b,c,d,e,f},{x,y}];
errortable=xyfit["ParameterTable"]

发代码老是被吞，照着抄一下吧，也没几句，data就是你的原始数据