afeddersen

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11 years, 65 days
I study psychology and economics with a very quantitative approach to each. I specialised on statistical methods, quantitative diagnostics, portfoio analysis and econometrics. Furthermore I am interested (and above that theoretically and empirlcally involved) in poker, chess and performing arts.

MaplePrimes Activity


These are replies submitted by afeddersen

You are right and I was wrong.

Thanks for clarification.

You are right and I was wrong.

Thanks for clarification.

Both comments were very useful to me.

Both comments were very useful to me.

@acer 

I see your point. Thanks for clarification on this.

@acer 

I see your point. Thanks for clarification on this.

Are you sure your way is doing what I intended?

Compare EY (your suggestion) and EG (computation of expected utility without using 'ExpectedValue'):

with(Statistics):
assume(mu::real,sigma>0);
X:=RandomVariable(Normal(mu,sigma)):
Y:=RandomVariable(Distribution(PDF=subs(f=unapply(PDF(X,T),T),t->(1-exp(-phi*t))*f(t)))): #I used a specific function u(t)
EY:=ExpectedValue(Y);

EG:=int(1/(sqrt(2*Pi)*sigma)*exp(-(t-mu)^2/(2*sigma^2))*(1-exp(-phi*t)),t=-infinity..infinity);

I am not sure how to show efficiently with Maple, if those two expressions are different, but evaluating at specific points outputs different values though.

Thanks for answering.

Are you sure your way is doing what I intended?

Compare EY (your suggestion) and EG (computation of expected utility without using 'ExpectedValue'):

with(Statistics):
assume(mu::real,sigma>0);
X:=RandomVariable(Normal(mu,sigma)):
Y:=RandomVariable(Distribution(PDF=subs(f=unapply(PDF(X,T),T),t->(1-exp(-phi*t))*f(t)))): #I used a specific function u(t)
EY:=ExpectedValue(Y);

EG:=int(1/(sqrt(2*Pi)*sigma)*exp(-(t-mu)^2/(2*sigma^2))*(1-exp(-phi*t)),t=-infinity..infinity);

I am not sure how to show efficiently with Maple, if those two expressions are different, but evaluating at specific points outputs different values though.

Thanks for answering.

Thanks acer,

I learned something new. In fact I didn´t know, that the Digits environment variable controls the working precision and that the effect of round-off error could be that significant.

So may I also manipulate the working precision of the 'Explore' option by setting 'Digits' to another value (say 20) or is there another way of minimizing the round-off error effects when using 'Explore'?

Thanks acer,

I learned something new. In fact I didn´t know, that the Digits environment variable controls the working precision and that the effect of round-off error could be that significant.

So may I also manipulate the working precision of the 'Explore' option by setting 'Digits' to another value (say 20) or is there another way of minimizing the round-off error effects when using 'Explore'?

Indeed I thought that this assumption might help.

Anyway, your suggestion of using 1+X1 instead of X1 helped a lot. This is compatible with ln(x) and yields no zero values.

Thanks for your help.

Indeed I thought that this assumption might help.

Anyway, your suggestion of using 1+X1 instead of X1 helped a lot. This is compatible with ln(x) and yields no zero values.

Thanks for your help.

Well, of course you are right for the usual domain of x.

Anyway by additionally using assumpions, I tried to limit the domain of x to positive integers.

If I did it the wrong way I may ask you to correct me and tell me how to do better.

Well, of course you are right for the usual domain of x.

Anyway by additionally using assumpions, I tried to limit the domain of x to positive integers.

If I did it the wrong way I may ask you to correct me and tell me how to do better.

@Alejandro Jakubi 

Thanks for your remark.

Until now I always had a constant "feeling" that there must be a difference between assume and assuming.

Now I know at least one aspect of their heterogeneousness.

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