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The relation between local and global truncation errors is slightly different from in the simpler setting of one-step methods. For linear multistep methods, an additional concept called zero-stability is needed to explain the relation between local and global truncation errors.
Estimation of truncated regression models is usually done via parametric maximum likelihood method. More recently, various semi-parametric and non-parametric generalisation were proposed in the literature, e.g., based on the local least squares approach [5] or the local maximum likelihood approach, [6] which are kernel based methods.
1 Examples. Toggle Examples subsection. 1.1 Infinite series. 1.2 Differentiation. ... Example A: Find the truncation in calculating the first derivative of () = ...
In statistics, truncation results in values that are limited above or below, resulting in a truncated sample. [1] A random variable y {\displaystyle y} is said to be truncated from below if, for some threshold value c {\displaystyle c} , the exact value of y {\displaystyle y} is known for all cases y > c {\displaystyle y>c} , but unknown for ...
Lady Windermere's Fan (mathematics) — telescopic identity relating local and global truncation errors Stiff equation — roughly, an ODE for which unstable methods need a very short step size, but stable methods do not
Occupancy Grid Mapping refers to a family of computer algorithms in probabilistic robotics for mobile robots which address the problem of generating maps from noisy and uncertain sensor measurement data, with the assumption that the robot pose is known. Occupancy grids were first proposed by H. Moravec and A. Elfes in 1985.
In statistics, a truncated distribution is a conditional distribution that results from restricting the domain of some other probability distribution.Truncated distributions arise in practical statistics in cases where the ability to record, or even to know about, occurrences is limited to values which lie above or below a given threshold or within a specified range.
[1] [2] The key property of a PML that distinguishes it from an ordinary absorbing material is that it is designed so that waves incident upon the PML from a non-PML medium do not reflect at the interface—this property allows the PML to strongly absorb outgoing waves from the interior of a computational region without reflecting them back ...