First of all, hello all this is my first post i think. Congratulations on this great community(adsbygoogle = window.adsbygoogle || []).push({});

Please move my post if I'm not posting on the right forum and I'm sorry for any inconvenience.

I have this problem that I need to solve and I don't have a clue. I hope you could give me some ideas.

I need to show this: [tex]\mathop {\sup }\limits_\theta \left\| {E_\theta \left( {\hat \beta _T } \right) - b\left( \theta \right)} \right\| \to 0[/tex]

knowing that:

[tex]\hat \beta _T \stackrel{T\rightarrow\infty}{\rightarrow} b\left( {\theta _0 } \right)[/tex]

where [tex]\hat \beta _T[/tex] is a stochastic function of [tex]y_T[/tex] that comes from a distribution with true parameter [tex]\theta_0[/tex]

θ and β belongs in a compact subset of R^p and R^q respectively.

The convergence apparently is non-stochastic as we've taken expectation.

A hint is to add and subtract something into the norm and use the triangle inequality to show the above claim. But, I have no idea how to treat the expectation.

I haven't supplied all info there is, but please tell me if you can think of any possible approaches for this. Any help is much appreciated

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# Uniform Convergence problem

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