A strong law of large numbers for identically distributed vector lattice-valued random variables
Convergence of weighted sums of random variables in vector lattices
On the expected value of vector lattice-valued random variables
On relatively uniform convergence of weighted sums of -lattice valued random elements
The strong law of large numbers for o-convergent random variables
On random variables having values in a vector lattice
On a property of Riesz spaces
On the extension of measures
Strong laws of large numbers for double sequences of random elements
On parameter-effects arrays in non-linear regression models
Formulas for a new three- and four-dimensional parameter-effects arrays corresponding to transformations of parameters in non-linear regression models are given. These formulae make the construction of the confidence regions for parameters easier. An example is presented which shows that some care is necessary when a new array is computed.
Confidence regions in nonlinear regression models
New curvature measures for nonlinear regression models are developed and methods of their computing are given. Using these measures, more accurate confidence regions for parameters than those based on linear or quadratic approximations are obtained.
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