汽车高斯曲面拟合

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2程序，以适应到表面二维高斯：



子= A *的进出口（ -（（西为X0）^2/2/sigmax^2 +（艺Y0的）^2/2/sigmay^ 2）。。）+ b的



这些例程是自动在某种意义上说，他们并不需要出发对模型参数的猜测规范。



autoGaussianSurfML（十一，彝，子）适合通过对模型参数的最大似然（最小二乘）。它首先计算了该模型在许多可能的参数值，然后选择最佳质量设置和细化与lsqcurvefit它。



autoGaussianSurfGS（十一，彝，紫）的估计，通过指定数据的贝叶斯生成模型，然后采取通过从模型吉布斯抽样样本后ofthis模型参数。这种-Auto Gaussian Surface fit

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2 routines to fit a 2D Gaussian to a surface:



zi = a*exp(-((xi-x0).^2/2/sigmax^2+ (yi-y0).^2/2/sigmay^2))+ b



The routines are automatic in the sense that they do not require the specification of starting guesses for the model parameters.



autoGaussianSurfML(xi,yi,zi) fits the model parameters through maximum likelihood(least-squares). It first evaluates the quality of the model at many possible values of the parameters then chooses the best set and refines it with lsqcurvefit.



autoGaussianSurfGS(xi,yi,zi) estimates the model parameters by specifying a Bayesian generative model for the data, then taking samples from the posterior ofthis model through Gibbs sampling. This method is insensitive to local minimain posterior and gives meaningful error bars (Bayesian confidence intervals)