|
|
 |
| Авторизация |
|
|
|
| Поиск по указателям |
|
|
|
|
|
|
|
 |
|
|
|
| Bates Douglas M., Watts Donald G. — Nonlinear Regression Analysis and Its Applications (Wiley Series in Probability and Statistics) |
|
|
|
| Предметный указатель |
Klema, V.C. 316 317
Kuh, E. 1 26
Lack of fit 29
Lack of fit, analysis, nitrite example 113
Lack of fit, degrees of freedom 29
Lack of fit, mean square 29
Lack of fit, sum of squares 29
Lag 92
Lawton, W.H. 69
Least squares criterion 25
Least squares estimate 5
Least squares estimates for nonlinear model 39
Least squares geometry 39
Least squares geometry of nonlinear 43
Least squares properties of estimator 5
Levenberg — Marquardt compromise 80 81
Levenberg, K. 81
Lewis, M. 74 273
Likelihood 60
Likelihood, conditional 204
Likelihood, contour 6 200
Likelihood, function 4 23 25
Likelihood, geometry 23
Likelihood, inference 6
Likelihood, interval 205
Likelihood, profile trace 207
Likelihood, region 6 200 256
Likelihood, region, scaled 242
Lindstrom, M.J. 86
Linear approximation 64
Linear approximation to expectation function 40 229 232
Linear approximation to expectation surface 232
Linear approximation to obtain Gauss — Newton increment 64
Linear approximation to sum of squares function 61
Linear approximation, inference band 58
Linear approximation, inference interval 58
Linear approximation, inference region 64 200 232
Linear model 2
Linear regression 1
Linssen, H.N. 87 274
Lisk, D.J. 3 267
Loglikelihood, conditional 138
Loglikelihood, function 60
Lucas, H.L. 124 125
Lythgoe, S.C. 311
MacGregor, J.F. 135 147 148 155 156 157 272
Maggio, M.S. 69
Marquardt, D.W. 81
Marske, D. 41 270 305
Matrix, centered data 155
Matrix, covariance 137
Matrix, derivative 40
Matrix, effective residual curvature 260
Matrix, expected response 136
Matrix, exponential 172 173
Matrix, hat 27
Matrix, observation 136
Matrix, parameter correlation 54
Matrix, relative curvature 244
Matrix, residual 136 155
Matrix, singular 155
Matrix, system transfer 148 171
Maximum likelihood estimate 5 138
McLean, D.D. 155 156
Missing data in multiresponse estimation 164
Model assessment 23 26
Model, linear differential equations 168
Model, nested 103 162
Model, non-nested 103
Model, selection, nitrite example 113
Model, specification in nonlinear regression 67
Model, unidentifiable 181
Moler, C.B. 13 81 145 156 244 289 295 302 316 317
Montgomery, D.C. vii 1 28
Multiresponse estimation 134
Multiresponse estimation, advantages and disadvantages 141
Multiresponse estimation, assessing fit 149
Multiresponse estimation, compartment model 188
Multiresponse estimation, convergence criterion 145
Multiresponse estimation, dependencies in data 154
Multiresponse estimation, missing data 164
Multiresponse estimation, model 134
Multiresponse estimation, practical considerations 146
Murray, W. 77
Negami, S. 136 146 280
Nested model 103
Nested model, extra determinant test 162
Newton — Raphson iteration method 79
Nonlinear least squares via sums of squares 60
Nonlinear model 32
Nonlinear model — intrinsically linear 34
Nonlinear model — transformably linear 34
Nonlinear regression 32 67
Nonlinearity and profile t plot 205
Nonlinearity and profile traces 207
Nonlinearity of model-data set 62
Nonlinearity, intrinsic 237 256
Nonlinearity, parameter effects 237
Nonlinearity, relative curvature measures 232
Normal assumption 25 91
Normal distribution 2 25
Normal equations 12
Normal plot 91
Normal probability plot 27
Normal spherical distribution 9 16 33
Oneill, B. 220
Orthogonal basis 13
Orthogonal transformation 16
Outlier 27
Overparametrization 87 90
Overparametrization, nitrite example 116
Overshoot 64
p-value 17
Parameter effects, curvature 241
Parameter effects, curvature — geometric interpretation 246
Parameter effects, nonlinearity 237
Parameter effects, relative curvature array 242
Parameter transformation, centering and scaling 78
Parameter transformation, to improve convergence 78
Parameter, approximate correlation matrix 90
Parameter, approximate correlations 53
Parameter, approximate covariance matrix 85
Parameter, approximate inference region 52
Parameter, approximate standard error 53
Parameter, arcing 247
Parameter, as functions of other variables 108
Parameter, compansion 247
Parameter, conditionally linear 36 76 85
Parameter, confidence interval 6
Parameter, constraint 77
Parameter, correlation matrix 54
Parameter, curve 45
Parameter, exchangeable 78 180
Parameter, extra degrees of freedom 103
Parameter, fanning 247
Parameter, incremental 91 104
Parameter, inference region 15 52
Parameter, kinetic 188
Parameter, line 10
Parameter, line on expectation surface 39
Parameter, linear approximation line to curve 45 47
Parameter, nonlinearity 237
Parameter, nuisance 26
Parameter, plane 10 38
Parameter, process 108 188
Parameter, t ratio 90
Parameter, torsion 247
Parameter, transformation 179 248
Parker, J.O. 69
Partial autocorrelation function 94
| Peck, E.A. vii 1 28
Peeling 74 97
Peirson, D.R. 110 278
Pereyra, V. 81 86 142
Planar assumption 43 45 229 232 256
Planar assumption and intrinsic curvature 245
Plot of residuals 27
Plot, fitted and observed 91
Plot, lag 92
Plot, residual vs fined 91
Plot, time series 92
Posterior density 7
Posterior density for nonlinear model 219
Posterior density, profile trace 222
Practical considerations, accumulated data 96
Practical considerations, assessing fit 90
Practical considerations, check for convergence 90
Practical considerations, collinearity 78 80
Practical considerations, comparing models 103
Practical considerations, compartment models 179
Practical considerations, conditionally linear parameter 85
Practical considerations, constraint on parameter 77
Practical considerations, correlated residuals 92
Practical considerations, derivative-free methods 82
Practical considerations, disturbance 69
Practical considerations, improving convergence 78
Practical considerations, in multiresponse estimation 146
Practical considerations, in nonlinear regression 67
Practical considerations, Levenberg — Marquardt compromise 80 81
Practical considerations, model specification 67
Practical considerations, modifying the model 90
Practical considerations, numerical derivatives 82
Practical considerations, obtaining convergence 86
Practical considerations, parameters as functions of other variables 108
Practical considerations, preliminary analysis 70
Practical considerations, presenting the results 109
Practical considerations, QR decomposition 80
Practical considerations, starting values 72
Practical considerations, starting values for compartment models 182
Practical considerations, unidentifiable model 180
Preliminary analysis, nitrite example 110
Prior density for nonlinear model 216
Prior density on expectation surface 217
Prior density, noninformative 7
Pritchard, D.J. 155 156 306
Probability density function 2 24
Profile pair sketches 209
Profile t 205
Profile trace 207
Profile trace, posterior 222
QR decomposition 13
QR decomposition of residual matrix 141
QR decomposition of velocity and acceleration matrix 236
Ralston, M.L. 49 82 85
Random variable 1 24
Randomization 24 25 26 123
Rate constant 168 179
Ratkowsky, D.A. 72 213 215 249
Relative curvature 241
Relative curvature, algorithm 244
Relative curvature, array 242
Relative curvature, matrix 244
Renwick, A.G. 97 101 277 306
Reparametrization 248
Reparametrization and parameter effects 238
Replication 24 28 36 70 123 126
Replication, degrees of freedom 29
Replication, importance of 26
Replication, mean square 29
Replication, sum of squares 29
Report, writing 109
Residual 4 24 40 90
Residual, autocorrelation function 94
Residual, correlated 92
Residual, degrees of freedom 29
Residual, matrix 136 155
Residual, mean square 6 30
Residual, normal probability plot 91
Residual, plot 91 149
Residual, studentized 27
Residual, sum of squares 4 29
Residual, vector 12 139
Residual, vector, approximate 260
Response, function confidence band 6
Response, space 10 36
Robinson, W.E. 170 188 282
Roller, D. 268
Root mean square (RMS), curvature 254
Ruppert, D. 70 91
Sampling distribution 25
Sampson, P.F. 49
Schnabel, R.B. 80 82 145
Seber, G.A. 1 5 25
Second derivative array 233 250
Serum, J.W. 3 267
Sigma-minus method for accumulated data 97
Silvey, S.D. 123
Singular data matrix 155
Singular residual matrix 155
Singular value decomposition 156
Smith, B.T. 316 317
Smith, H. vii 1 26 28 49 70 91 123
Sorensen, J.P. 68 164 165
Sredni, J. 92 274
St. John, R.C. 123
Stabilizing variance 28
Standard error 7 21
Standard error, approximate 53
Starting values 72
Starting values for compartment model 182
Starting values, conditionally linear model 76
Starting values, interpreting derivatives of expectation function 73
Starting values, interpreting expectation function 72
Starting values, multiresponse 146
Starting values, peeling 74
Starting values, reducing dimensions 76
Starting values, systems of differential equations 147
Starting values, transformably linear model 73
Starting values, transforming expectation function 73
Steepest descent 81
Steinberg, D.M. 123 131
Step factor 42 64 84 85 145
Stewart, G.W. 13 81 145 156 244 289 295 302 316
Stewart, W.E. 68 69 164 165 168 179
Stiratelli, R.G. 96 274
Sum of squares 4
Sum of squares, contour 23 61
Sum of squares, extra 103
Sum of squares, function 60
Sum of squares, lack of fit 29
Sum of squares, replication 29
Sum of squares, residual 29
Sylvestre, A. 69
System diagram 169
t distribution 6 7
T distribution, multivariate 7 139 220
Tail probability 17
Tangent plane 43
Tangent plane, approximation to expectation surface 44 45 232
Tangent space dimension 234
Tiao, G.C. 1 7 139 140 218 220
Tidwell, P.W. 3
Tierney, L. 223
Time series 92
Time series, autoregressive model 93
Time series, moving average model 93
Titterington, D.M. 123
Torsion 247
Trace, criterion for multiresponse estimation 136
Transfer matrix 148 171
|
|
|
| Реклама |
|
|
|
|
|
О проекте