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增长曲线模型中的条件最优线性无偏预测 被引量:2

Conditional Optimal Linear Unbiased Prediction in General Growth Curve Model
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摘要 研究了带线性等式约束下增长曲线模型中条件可预测变量的最优预测。考虑了一类特殊的预测函数:Φ-线性预测函数,给出了条件Φ-线性可预测变量和条件最优Φ-线性无偏预测的定义。在一定条件下分别得到了条件最优线性无偏预测和条件最优Φ-线性无偏预测,并证明了它们在几乎处处意义下的唯一性。 The problem of conditional optimal prediction for conditional linear predictable variable in the general growth curve model is investigated. A class of special prediction function is considered: Ф- linear prediction function. The conditional optimum Ф-linear unbiased predictors of conditional Ф-linear predictable variable is obtained. The results show that any conditional optimum linear unbiased predictors are unique with probability one.
作者 黄介武
出处 《长沙交通学院学报》 2006年第2期68-71,共4页 Journal of Changsha Communications University
关键词 增长曲线模型 条件最优线性无偏预测 条件最优Ф一线性无偏预测 general growth curve model conditional optimal linear unbiased prediction conditionaloptimum Ф-linear unbiased prediction
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参考文献9

  • 1Pereira C A B,Rodrigues J. Robust linear prediction in finite populations[J]. International Statistical Review. 1983,51:293- 300.
  • 2Bolfarine H, Pereira C A B, Rodrigues J. Linear prediction in finite populations-a bayesian perspective[J]. Sankhya (Series B), 1987,49 : 23-35.
  • 3Bolfarine H, Rodrigues J. On the simple projection predictor in finite populations[J]. Australian Journal of Statistics, 1988,30 : 338-341.
  • 4Bolfarine H, Zacks S. Bayes and minimax prediction in finite populations[J]. Journal of Statistical Planning and Inference, 1991,28 : 139-151.
  • 5Bolfarine H, Zacks S, Elian S N, et al. Optimal prediction of the finite population regression coefficient[J]. Sankhya(Series B), 1994,56 : 1-10.
  • 6Rodrigues J, Bolfarine H, Rogaktoa A. General theory of prediction in finite population[J]. International Statistical Review, 1985,53 : 239-254.
  • 7喻胜华,何灿芝.任意秩多元线性模型中的最优预测[J].应用数学学报,2001,24(2):227-235. 被引量:35
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二级参考文献8

  • 1[1]Pereira C A B, Rodrigues J. Robust Linear Prediction in Finite Populations. International Statistical Review, 1983, 51:293-300
  • 2[2]Bolfarine H, Pereira C A B, Rodrigues J. Robust Linear Prediction in Finite Populations-A Bayesian Perspective. Sankhya-(Series B), 1987, 49:23-35
  • 3[3]Bolfarine H, Rodrigues J. On the Simple Projection Predictor in Finite Populations. Aust. Jour.Statist., 1988, 30:338-341
  • 4[4]Bolfarine H, Zacks S. Bayes and Minimax Prediction in Finite Populations. Jour. Statistical Planning and Inference, 1991, 28:139-151
  • 5[5]Bolfarine H, Zacks S, Elian S N, Rodrigues J. Optimal Prediction of the Finite Population Regression Coefficient. Sankhya- (Series B), 1994, 56:1-10
  • 6[6]Rodrigues J, Bolfarine H, Rogakto A. A General Theory of Prediction in Finite Populations. International Statistical Review, 1985, 53:239-254
  • 7李俊海,徐兴忠,陈峥.增长曲线模型中向量函数的线性可容许性[J].应用概率统计,2000,16(2):145-151. 被引量:5
  • 8喻胜华,何灿芝.任意秩多元线性模型中的最优预测[J].应用数学学报,2001,24(2):227-235. 被引量:35

共引文献36

同被引文献13

  • 1袁权龙.一般生长曲线模型中的简单投影预测[J].福州大学学报(自然科学版),2006,34(6):803-805. 被引量:2
  • 2Bolfarine H, Rodrigues J. On the simple projection predictor in finite populations[ J]. Aust Jour Statist, 1988,30:338 - 341.
  • 3杨婷 杨虎 张洪阳 重庆.基于岭估计的最优预测与经典预测的最优性判别.重庆大学学报,2002,(6):56-58.
  • 4Pereira C A B, Rodrigues J. Robust linear prediction in finite populations [ J ]. International Statistical Review, 1983,51 : 293 - 300.
  • 5Bolfarine H, Pereira C A B, Rodrigues J. Linear prediction in finite populations-a bayesian perspective[ J ]. Sankhya( Series B), 1987,49.23 - 35.
  • 6Bolfarine H, Rodrigues J. On the simple projection predictor in finite populations[ J ]. Aust Jour Statist, 1988,30:338 - 341.
  • 7Bolfarine H, Zacks S. Bayes and minimax prediction in finite populations[J]. Jour Statistical Planning and Inference, 1991, 28:139-151.
  • 8Bolfarine H, Zacks S, Elian S N, et al. Optimal prediction of the finite population regression coefficient[ J ]. Sankhya( Series B), 1994,56:1 - 10.
  • 9Rodrigues J, Bolfarine H. Rogaktoa. A General theory of prediction in finite population[ J ]. International Statistical Review, 1985,53:239 - 254.
  • 10Bibby J, Toutenburg H. Prediction and inproved estimation in linear models[M]. New York: Wiley, 1977.

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