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We then move to the bivariate setting in the next section as a direct extension of this approach.
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These theoretical properties are used to develop an asymptotic theory of maximum likelihood estimation for the GMVAR model whose practical usefulness is illustrated in a bivariate setting by examining the relationship between the EUR USD exchange rate and a related interest rate data.
In the "Methods" section a bargaining model is developed that first involves the SHI association and a MCO in a bivariate setting, representing the status quo.
In the case of bivariate sets of signals (i.e. recorded in two distant locations of the uterus), which contain two simultaneously recorded time series, it appears clinically important to understand how the variables interact.
In Section 2, we first motivate our construction for the bivariate set-up with a simple case starting from a symmetric Binomial distribution.
We compute the power of this newly derived test via simulation for various alternative hypotheses in a bivariate set up for unbalanced designs and observe that power responds sharply when sample size and alternative hypotheses are changed.
Set in the sunlight.
Hence, we will propose the bivariate case in the following.
Setting up an explicit statistical model that links costs and effects has proved challenging beyond the bivariate normal situation (in which the incremental costs and effects follow a bivariate normal distribution).
Set the in-betweens.
Due to multicolinearity among predictors, 10 exchangeable bivariate prediction sets were constructed consisting of (1) TNFα expression in either the intimal lining layer or synovial sublining with (2) one out of five cellular markers.
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