B
bias parameters, 10
C
class hierarchy, 7
condition equations, 11
covariance matrix, 10
D
derived classes, 6
E
Ephemeris Generation, 13
extensibility, 3, 7
F
Figure 1, 4
Figure 2, 6
Figure 3, 7
Figure 4, 9
Formal Parameter Errors, 10
I
inheritance, 3, 6, 7
integration module, 4, 13
Introduction, 3
J
JPL, 3
L
least squares, 4, 5, 9, 10, 11
Linear Parameter Estimation, 9
M
maximum likelihood, 9
measurement errors, 11
merit function, 12
model function, 10, 11
N
Newcomb, 3
Nonlinear Parameter Estimation, 11
normal equations, 9, 10, 11
O
Observation Types, 7
observational errors, 9, 11
observations module, 4, 6
Observing Platforms, 6
O-C, 4, 6, 9
P
paraboloidal approximation, 12
parameter adjustment, 4, 6, 9
Parameter Adjustment Module, 9
parameter correlations, 5
parameter variance, 11
PEP, 3, 5
Physical Model, 13
Project Outline, 3
propagation of errors, 10, 11
R
random errors, 10
residuals, 4, 9
S
singular value decomposition
SVD, 3, 9
Index
Index
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