The exponential models with additive noise describe a class of important nonlinear stochastic systems.
鉴于含有加性噪声的指数模型描述了一类重要的非线性随机系统。
In Chapter 4, we discuss and prove the consistency and asymptotic normality of maximum likelihood estimate to the exponential models.
第四章讨论了序贯指数模型的极大似然估计的强相合性和渐近正态性，并进行了证明。
Within the method of first-order trend OK, Gaussian semi-variogram model performed better than both the spherical and exponential models.
一阶趋势的OK方法中半方差函数模型选用高斯型的比选用球状和指数型的插值效果相对要好。
Within the method of first-order trend OK, Gaussian semi-variogram model performed better than both the spherical and exponential models.
一阶趋势的OK方法中半方差函数模型选用高斯型的比选用球状和指数型的插值效果相对要好。
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