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comment Fast Hankel Transform
it is the discretized version of $J_o(\lambda r)$
May
20
reviewed Approve A question in signals and systems
May
20
comment A question in signals and systems
use the definitions. I think you musnt ask such a question here which directly follows from the definitions. simply write down the definitions of linearity and memory then apply the definitions to your specific example.
May
18
revised Correctness of a statistical evaluation of a parameter
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May
18
comment Correctness of a statistical evaluation of a parameter
$c$ is the tolerance parameter in the above given setting. For example if $c=1.345$, then this corresponds to $95\%$ efficiency of the estimator for the normal distribution. If there is a predefined tolerance as $1.5\%$, then yes, it is the $3$ sigma rule and it means one needs to consider only the values lying in $3$-sigma for the estimation. On the other hand, if some data samples are not observable, then there may be a bias upto some degree. In this case the approach would be bias correction.
May
18
answered Correctness of a statistical evaluation of a parameter
May
15
comment Correctness of a statistical evaluation of a parameter
The last figure is the histogram of your parameter calculated over all possible values it takes right? 3 sigma rule is just a rule of thumb to avoid outlying observations. There are much better ways than that.
May
14
reviewed Approve Multivariable calculus integration over a rectangle
May
13
revised Maximum likelihood estimator on uniform distribution
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May
13
revised Maximum likelihood estimator on uniform distribution
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May
13
comment Maximum likelihood estimator on uniform distribution
Okay just wait. Then I edit the answer.
May
13
comment Maximum likelihood estimator on uniform distribution
Yes, it means I know the answer already but I want to hear something from you. It is always better for you, not for me. Okay, I give you another hint: you seem to forget $0 \leq x_n \leq \theta$
May
13
answered Maximum likelihood estimator on uniform distribution
May
9
comment uncertainty of slope.
Both are some measures of uncertainty.
May
8
revised Can someone intuitively explain what the convolution integral is?
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May
6
revised Find density function of $X + Y$ , where $X, Y$ random variables.
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May
6
comment Find density function of $X + Y$ , where $X, Y$ random variables.
@Billie this is not a good sign. because this is something really basic. any bivariate density has $3$ components $x$ and $y$ shows you where the things happen and $z$ component shows you how much it happens. Namely the value of the density at $(x,y)$, $f(x,y)$, so $f(x,y)=2$
May
6
comment Find density function of $X + Y$ , where $X, Y$ random variables.
@Billie it is the area of the triangle given by the points $(0,0)$, $(0,z)$ and $(z,0)$ multiplied by $2$. Did you understand why we must multiply with $2$?
May
5
answered Find density function of $X + Y$ , where $X, Y$ random variables.
May
5
comment Problem with the Birthday Problem
your approach if fundamentally wrong.