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Statistical simulation is defined as a numerical method of solving mathematical problems. In this method, we represent the desired quantities as probabilistic characteristics of some random phenomenon, and by this way a mathematical model of the phenomenon is constructed. All the quantities that are needed are approximately determined by statistical analysis of “observations” on the model. Statistical simulation is found to be widely used for the computer solution of integral equations such as in the investigation of complex systems. This method is universally convenient and generally does not require a large memory. But a drawback of this system is the number of large random errors that decreases extremely as the number of experiments increases. Because of this reason, the methods model transformations that make it possible to decrease the spread of the observed quantities and the size of the modeling experiment have been worked out. The detail description and analysis of Statistical simulation is given by Statistical simulation Assignment Help Online.
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- Using stratified sampling
The most widely used sampling designs in official statistics are implemented in simFrame. In order to change to another sampling design, only the corresponding control object requires to be changed. We can perform stratified sampling by region using this method. The sample sizes are specified for different strata with the help of a vector for the slot size of the control object. The Complete details about sampling are given under Statistical Simulation Assignment Help.
It is needed for increase of contamination to the data to study the influence of these outliers on the robust estimators and their classical counterparts. In simFrame, by defining a control object, we specify the contamination. There are various contamination models that are implemented in the framework. The full details can be studied under Statistical Simulation Assignment help.
- Performing simulations separately on different domains
Data sets from official statistics specifically contain strong heterogeneities; therefore the indicators are usually calculated for subsets of the data as well. Therefore it is often of interest to investigate the behavior of indicators on different subsets in simulation studies. In simFrame, this can be done by simply specifying the argument of the design of the function used in the code.
- Multiple contamination levels
More than one level of contamination is typically investigated in simulation studies so that we can get a more complete picture of the behavior of the robust methods. The various techniques can be better understood and necessary materials can be provided by Statistical simulation assignment Help Online Service.
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