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Feb
19
comment Cobb-Douglas utility function
No, you are normalising utilities of different proportions using $U(1-\alpha,\alpha)$. To understand why $U(1-\alpha,\alpha)$ acts as some benchmark, we will need more context and the details of where you came across this.
Feb
19
answered order of integration and Fubini's theorem
Feb
19
answered A question dealing with the convexity of functions involving the absolute value
Feb
19
answered Cobb-Douglas utility function
Feb
19
answered Strong Markov property explained.
Feb
13
comment $\int_0^{\infty} \lim_{m \rightarrow \infty} x_m \left( \varepsilon \right) e^{- \varepsilon} \mathrm{d} \varepsilon$
@AntonioVargas: thanks, edited.
Feb
13
revised $\int_0^{\infty} \lim_{m \rightarrow \infty} x_m \left( \varepsilon \right) e^{- \varepsilon} \mathrm{d} \varepsilon$
added 12 characters in body
Feb
13
answered Monotonically increasing vs Non-decreasing
Feb
13
answered Expectation of characters in a string
Feb
13
answered $\int_0^{\infty} \lim_{m \rightarrow \infty} x_m \left( \varepsilon \right) e^{- \varepsilon} \mathrm{d} \varepsilon$
Feb
13
comment Constrained maximization problem
Sorry, I meant $\lambda_1=-1/z$ for interior $\alpha$. You get that from the third Lagrangian condition.
Feb
13
answered Probability…coin toss
Feb
13
comment Constrained maximization problem
@user39097: I do not see any trick, but $\lambda_1=-0.5$ it seems from calculations. $\alpha$ also gets eliminated, so perhaps it is not as daunting as you think it is.
Feb
13
answered Representing train schedules in a matrix
Feb
13
answered Constrained maximization problem
Feb
9
comment Expectation conditioned on a sigma algebra
Thanks did! That's has a nice intuition to have on discrete spaces.
Feb
9
accepted Expectation conditioned on a sigma algebra
Feb
9
suggested rejected edit on How to find indefinite integral $\int a^{\frac {1}{x}} \mathrm dx$?
Feb
9
revised Prove that $\mathrm{E}[X\mid A] = \mathrm{E}[X]$ for an event $A$ independent of random variable $X$
minor changes for clarity sake...
Feb
9
suggested approved edit on Prove that $\mathrm{E}[X\mid A] = \mathrm{E}[X]$ for an event $A$ independent of random variable $X$