Revision #584 → #1354 · back to history
addedLeast squares methodb8ad90ed3929
addedTwo categories of least squares problems14913243f0c9
addedPolynomial least squaresb402cd3edcf5
addedLeast squares equals maximum likelihood for exponential familiesee86eb7c047c
addedResidual34dc47c3e48a
addedSum of squared residuals minimization5f8234edc297
addedSimplest case yields the arithmetic mean645aa7f9c33e
addedStraight-line modelf3f78e0ba409
addedGradient set to zero0ccd64d2cd5f
addedLinear regression model15aa9417d80b
addedLinear least squares closed-form solutione4bfe0c129c8
addedIterative refinement for NLLSQ0d42115697ef
addedGauss–Newton normal equationsb48116396061
addedLinear vs nonlinear in parametersaa10383ae215
addedLLSQ global concavityeb709e2b457f
addedUniqueness vs multiple minima2f6ff63d8d13
addedUnbiasedness of LLSQ vs NLLSQ16a89d94affe
addedHooke's law springbc181b883542
addedParameter variance estimateb163cadecaeb
addedNormality of estimates under normal errorscaba6105f6c7
addedGauss–Markov theoremdfc8f198b182
addedLeast squares as maximum likelihood under normal errorsab600b23ecfa
addedWeighted least squaresbbdc011f9f81
addedHeteroscedasticitybb887ecb3953
addedFirst principal component55a01bc5213d
addedLeast-squares estimator as a measure92df75867aef
addedTikhonov regularization245cecf76cf8
addedLasso vs ridge regressioneead726790c0