Description Usage Arguments Details Value References See Also

This function generates a 3D array giving (Xn-X) in the notation of
the `ConvergenceConcepts`

package by Lafaye de Micheaux and Liquet for sample paths
with dimensions *=* `n999`

as first dimension, `nover`

*=* range of n
values as second dimension and number of items in `key`

as the third
dimension. It is intended to be used for checking convergence of `meboot`

in the context
of a specific real world time series regression problem.

1 2 |

`y` |
vector of data containing the dependent variable. |

`bigx` |
vector of data for all regressor variables in a regression or |

`trueb` |
true values of regressor coefficients for simulation. If |

`n999` |
number of replicates to generate in a simulation. |

`nover` |
number of values of n over which convergence calculated. |

`seed1` |
seed for the random number generator. |

`key` |
the subset of key regression coefficient whose convergence is studied
if |

`trace` |
logical. If |

Use this only when lagged dependent variable is absent.

Warning: `key=0`

might use up too much memory for large regression problems.

The algorithm first creates data on the dependent variable for a simulation using known
true values denoted by trueb. It proceeds to create `n999`

regression problems using the
seven-step algorithm in `meboot`

creating `n999`

time series for all variable
in the simulated regression. It then creates sample paths over a range of n values for
coefficients of interest denoted as `key`

(usually a subset of original coefficients).
For each key coefficient there are `n999`

paths as n increases. If `meboot`

algorithm
is converging to true values, the value of (Xn-X) based criteria for
"convergence in probability" and "almost sure convergence" in the notation of the
`ConvergenceConcepts`

package should decline.
The decline can be plotted and/or tested to check if it is statistically significant
as sample size increases. This function permits the user of `meboot`

working with a short
time series to see if the `meboot`

algorithm is working in his or her particular situation.

A 3 dimensional array giving (Xn-X) for sample paths with dimensions *=* `n999`

as first dimension, `nover`

*=* range of n values as second dimension
and number of items in `key`

as the third dimension ready for use in
`ConvergenceConcepts`

package.

Lafaye de Micheaux, P. and Liquet, B. (2009), Understanding Convergence Concepts:
a Visual-Minded and Graphical Simulation-Based Approach,
*The American Statistician*, **63**(2) pp. 173-178.

Vinod, H.D. (2006), Maximum Entropy Ensembles for Time Series Inference in Economics,
*Journal of Asian Economics*, **17**(6), pp. 955-978

Vinod, H.D. (2004), Ranking mutual funds using unconventional utility theory
and stochastic dominance, *Journal of Empirical Finance*, **11**(3), pp. 353-377.

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