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Upper Bound for $\mathbb{E}\left[\max_{j \in \mathcal{N}} h_{j}\right]$

Assume $\{h_j\}_{j\in \mathcal{N}}$ are independent Gamma random variables, each with potentially different distributions and parameters. I am looking for an upper bound for $\mathbb{E}\left[\max_{j \...
Lee White's user avatar
1 vote
1 answer
56 views

How to study the convergence of the sample mode for arbitrary probability spaces

(This is not the problem I actually care about, but an analogy with similar issues to the problem I'm actually considering.) Consider a probability space with i.i.d. random variables $X_i$ producing ...
cgmil's user avatar
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0 answers
42 views

An integral estimate involving Bergman kernel

Let $V$ be the normalized volume measure on $\mathbb D^2$ and $k : \mathbb D \times \mathbb D \longrightarrow \mathbb C$ be the Bergman kernel on $\mathbb D^2$ given by $$k(z,w) = \frac {1} {\left (1 -...
Anacardium's user avatar
1 vote
2 answers
236 views

Calderón–Zygmund/$L^p$ estimates for the linear heat equation

Let $C_r$ denote the open cylinder $$ C_r = \{(x,t) \in \mathbb R^{n+1} : |x| < r, -r^2 < t < 0\} $$ and consider a classical $C^{2,1}_{x,t}(C_1)$-solution to the linear heat equation $$ \...
Desura's user avatar
  • 233
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0 answers
31 views

What is the Fisher information matrix of the von Mises-Fisher distribution?

Assuming the von Mises-Fisher distribution as $$f_{p}(\mathbf{x}; \boldsymbol{\mu}, \kappa) = C_{p}(\kappa) \exp \left( {\kappa \boldsymbol{\mu}^\mathsf{T} \mathbf{x} } \right),$$ where $\kappa \ge 0$,...
Math_Y's user avatar
  • 287
2 votes
1 answer
128 views

Almost sure convergence of double averages of IID random variables

Let $ \{X_i\}_{i=1}^{P} $ and $ \{Y_j\}_{j=1}^{Q} $ be two sequences of independent and identically distributed (i.i.d.) random variables. $X_i$ and $Y_j$ are independent between all pairs of $i$ and $...
CWC's user avatar
  • 433
2 votes
1 answer
170 views

Equivalence of minimizing trace and determinant over matrix quadratic form in multivariate regression

Consider the multivariate regression model $$Y = XB + E$$ where $Y$ is $n \times p$ and corresponds to the dependent variables, $X$ is $n \times k$ and corresponds to the independent variables, $B$ is ...
respectableuser1's user avatar
1 vote
0 answers
148 views

conjecture for general form of minimax estimator

I had previously posed an overly ambitious version of this conjecture here, Form of minimax estimator, which was quickly shot down by Václav Voráček (on twitter) and Iosif Pinelis (MO answer in the ...
Aryeh Kontorovich's user avatar
1 vote
1 answer
341 views

Form of minimax estimator

Let $\Delta$ be the set of all probability distributions over $\mathbb{N}=\{1,2,\ldots\}$ and fix some $\mathcal{P}\subseteq\Delta$. Suppose additionally that $\Delta$ is endowed with some norm $||\...
Aryeh Kontorovich's user avatar
1 vote
0 answers
104 views

Estimate for the gradient of solutions in an elliptic differential equation in a Sobolev space

Let $\Omega$ be a bounded or unbounded domain in $\mathbf R^{3}$ with a smooth boundary $S$ and a normal vector given by $n$. Now, we consider the following second-order elliptic problem with Neumann ...
Javier Gargiulo's user avatar
1 vote
0 answers
66 views

Parameter estimation of a Taylor expansion

Let $a,b$ two real numbers, $\theta$ a real parameter and suppose that you have an analytic function of the form: $$ f_\theta(x)\triangleq \sum_{k\in\mathbb{N}}a_k(\theta)x^k \quad\forall x\in[a,b], $$...
NancyBoy's user avatar
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1 answer
937 views

Derivative of log-likelihood function for Gaussian distribution with parameterized variance

Suppose we have a parameter $\theta \in R^{n}$ that defines some noisy observation $z=\mu(\theta)+\eta, z\in R^{m}$ where the noise follows a Gaussian distribution whose covariance is a function of ...
JNL's user avatar
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7 votes
1 answer
567 views

Singular Fisher information matrix and existence of unbiased estimators

I'm doing some research into the Cramer-Rao bound for time of arrival localization and have come across a rather strange result: the FIM is singular, but there exists an unbiased estimator. My ...
JNL's user avatar
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0 answers
51 views

Estimation of Nonzero Coefficients of Binary Cylotomic Polynomials

I am reading Fouvry's paper https://msp.org/ant/2013/7-5/ant-v7-n5-p07-p.pdf . I am still confused on section 4.2 why $P\leq x^{\frac{20}{9}\gamma -\frac{2}{3}}\mathcal{L}^{-16}$ leads to estimate in ...
Laurence PW's user avatar
2 votes
0 answers
87 views

A complex problem involving densities (likelihood functions) and optimization

Consider the following autoregressive process with normal errors: \begin{equation}\label{7YlUV4i8nuO}\tag{I} y_t = \phi y_{t-1}+ u_t, \quad u_t \overset{iid}{\sim} N(0,\sigma^2) \end{equation} We ...
PSE's user avatar
  • 13
4 votes
2 answers
305 views

Generalization of van der Corput's estimate on oscillatory integrals

Question: Given exponents $0<\alpha<\beta$ and an interval $[a,b]\subset(0,\infty)$ are there constants $C,d>0$ such that for any $\lambda_1,\lambda_2\in\mathbb{R}$, $$\left|\int_a^be(\...
Joel Moreira's user avatar
  • 1,701
1 vote
0 answers
59 views

Functional approximation with derivatives

I am trying to solve a functional approximation problem. Consider a set of measurements of a d-dimensional state $\mathrm x \in \mathbb{R}^d$, together with velocities $\dot{\mathrm x}$ and ...
can't stop me now's user avatar
2 votes
0 answers
122 views

Comparing the truncated $\ell^{1}$-norm of polynomial coefficients with the supremum norm on the unit disc

Let $p=a_{0}+a_{1}z+\ldots+a_{n}z^{n}$ be a polynomial. Consider the following truncated $\ell^{1}$-seminorm of the coefficients of $p$: $$\|p\|_{\ell^{1},\text{trun.}}:=\sum_{k=1}^{n}|a_{k}|=\|p-a_{0}...
Calculix's user avatar
  • 321
2 votes
1 answer
142 views

DKW inequality for $L^1$-norm

Suppose that $X,X_1,X_2,X_3\dots$ is a sequence of $\mathbb{P}$-i.i.d. random variables supported in the interval $[0,1]$. Let $F$ be the cumulative distribution of $X$, i.e. $F(x):=\mathbb{P}[X \le x]...
Bob's user avatar
  • 123
3 votes
0 answers
113 views

Is the Kalman Filter computationally optimal for Kalman filtering?

Kalman filtering is known to be a recursive process that minimizes mean square error in linear problems. My question is: has anybody shown that this algorithm is computationally optimal, i.e. that you ...
Diego Méndez's user avatar
3 votes
1 answer
377 views

A problem of using Schauder estimate in the paper of Yau's proof of calabi conjecture

[This question is looking at the paper Yau, S.-T., On The Ricci Curvature of a Compact Kähler Manifold and the Complex Monge-Ampére Equation, I, Comm. Pure Appl. Math., 31 (1978) 339-411, doi:10.1002/...
Elio Li's user avatar
  • 809
0 votes
0 answers
21 views

Estimatives for elliptic systems involving the laplacian

Considering the problem \begin{equation} \left\{ \begin{array}[c]{11} \Delta(\Delta \chi -\chi) = 0 & \text{in } \Omega, \\ \Delta \chi -\chi = h_2 - h_1, & \text{on } \partial\Omega \\ \end{...
Bruno Mascaro's user avatar
0 votes
0 answers
106 views

Maximum likelihood estimator for power law with negative exponent

Background I have data that roughly follows a power law with a negative exponent (up to a point; also, the parameters of the "fit" were just guesstimated by eye as a demonstration): Now I ...
mapf's user avatar
  • 101
1 vote
0 answers
34 views

Correlating two matrices $A,B$ with stochastic dependency structure imposed by cross-validation

Consider a labelled data set $$D = \{(x_1, y_1),...,(x_n, y_n)\} $$ on which we want to evaluate a machine learning algorithm using $k$-fold cross validation with $m$ different random seeds. This ...
Joker123's user avatar
  • 153
0 votes
0 answers
132 views

How to estimate sums over arithmetic progressions?

For $x>1$ $$ N(x)=\sum_{0<n<x \\n \equiv 1 \pmod 4\\ n\text{ squarefree}} 1 $$ How to estimate $N(x)$'s order? (Like $N(x) \sim Ax$) Furthermore, for $n=p_1p_2\cdots p_v$, define $\alpha (n)=...
five's user avatar
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4 votes
1 answer
414 views

What journal(s) do you recommend for submitting a paper on a topic that spans information theory and estimation theory?

I've written a paper that a) demonstrates an equivalence between conditional complexity $K$($Y$|$X$) in information theory and the random component of an effect size estimate $r_{xy}$, and then b) ...
virtuolie's user avatar
  • 183
1 vote
1 answer
101 views

Estimating the average of two gaussians' mean with minimal squared error

This is a follow-up to my previous question. Assume that $X\sim \mathcal N(\mu_1,\sigma_1^2)$ and $Y\sim \mathcal N(\mu_2,\sigma_2^2)$. I want to estimate $\frac{\mu_1+\mu_2}{2}$ after observing $X,Y$....
R B's user avatar
  • 618
2 votes
1 answer
871 views

Estimating the average of two gaussians' mean

Assume that $X\sim \mathcal N(\sigma_1,\mu_1)$ and $Y\sim \mathcal N(\sigma_2,\mu_2)$. I want to estimate $\frac{\mu_1+\mu_2}{2}$ after observing $X,Y$. In my setting, $\sigma_1,\sigma_2$ are known ...
R B's user avatar
  • 618
2 votes
0 answers
225 views

Sobolev (Triebel-Lizorkin) norm estimate for $F \circ u - F \circ v$

Let $F \in C^1(\mathbb R^d;\mathbb R)$ be such that $F(0) = 0$ and $$|F'(\tau v + (1 - \tau)w)| \leq \mu(\tau)(G(v) + G(w))$$ for some $\mu \in L^1([0,1])$ and some non-negative $G \in C^0(\mathbb R^d;...
Desura's user avatar
  • 233
4 votes
1 answer
339 views

Showing that $\sum_{n=0}^\infty (4n+1)q^{\left (\frac{4n+1}{2}\right)^2} - \sum_{n=1}^\infty (4n-1)q^{\left (\frac{4n-1}{2}\right)^2} \geq 0.1$

Recently I came along the following problem concerning a lower bound on the difference of two series: I want to show that for every $q \in [e^{-2},e^{-\frac{1}{2}}]$ we have $$ f(q) := \sum_{n=0}^\...
J. Swail's user avatar
  • 437
1 vote
0 answers
81 views

Calculating the mean squared error for an estimate of a large sum

Consider the set of all Boolean function $f: \{0, 1\}^{n} \rightarrow \{-1, 1\}$. Now, let's pick a function uniformly at random from this set. Let $F$ be the random variable corresponding to the ...
RandomMatrices's user avatar
2 votes
0 answers
78 views

Distribution of unbiased estimator of covariance matrix with missing values

Initial setup Assuming $X_1, ..., X_n \in \mathbb{R}^m$ are iid, sampled from $\mathcal{N}(\mu, V)$, one can define the estimators for the sample mean $\hat{\mu} = \frac{1}{n} := X^T 1_n$, and sample ...
user43389's user avatar
  • 255
2 votes
0 answers
130 views

L1 error of estimators

I came across the following problem and I have no clue how to approach it. I am looking for help with directions or references. Consider the $\alpha$-stable distribution with unknown true mean $\mu$, ...
Robert's user avatar
  • 173
0 votes
1 answer
121 views

How to detect, track and map a Markov chain

You are receiving a time series whose elements belong to a finite set. Assume the time series is distributed as a Discrete-Time Markov Chain. You receive one element at each time step. For each time ...
Diego Méndez's user avatar
2 votes
0 answers
139 views

'Contraction-like' inequality: how to deal with the boundary term?

I am interested in the following problem. Let $D = \mathrm{diag}(d_1, d_2, \ldots, d_n) \in \mathbb{R}^n$ be positive definite, let $B, K \in \mathbb{R}^n$, and let $G\in L^\infty((0, T)\times (0, L);...
user344045's user avatar
2 votes
1 answer
269 views

Spline Interpolation error of higher degree

It is well-known that the interpolation error of a cubic spline has at best order $O(h^4)$, which results from polynomials of degree $3$. Can I assume that, if one uses polynomials of degree $p$ and ...
Astraeus's user avatar
1 vote
0 answers
75 views

Percentile interval Lemma

Let $\theta$ be a parameter and $\hat{\theta}$ the plug-in estimate, I need a proof of the following lemma, as given in [1], p. 173, in the form of a reference or of a direct argument: Percentile ...
Roberto Palermo's user avatar
1 vote
0 answers
108 views

Bootstrap-$t$ confidence intervals

I'm writing a dissertation about bootstrap methods and the main book I'm using is Efron, B., & Tibshirani, R.J. (1994), An Introduction to the Bootstrap (1st ed.), Chapman and Hall/CRC. Now I need ...
Roberto Palermo's user avatar
2 votes
1 answer
154 views

Stability estimates on quotients of the form $ \frac{\prod_{j=1}^n a_j}{\prod_{j=1}^n b_j} $

Suppose that $a_j,b_j \in \mathbb C$ are complex numbers, $j=1,\dots,n$, with the property that $|a_j|,|b_j| \geq c > d >0$ where $c,d$ are positive real numbers. I'm interested in the stability ...
Muzi's user avatar
  • 173
2 votes
0 answers
90 views

The optimality of Kalman filtering

It is known that the Kalman filter estimates the state of the following system recursively. $$x_{k+1}=Ax_k+w_k, \ \ w_k \sim \mathcal{N}(0,Q)$$ $$y_k=Cx_k+v_k, \ \ v_k \sim \mathcal{N}(0,W)$$ In the ...
Jing Zhou's user avatar
3 votes
1 answer
139 views

Design a random variable which has the maximal correlation with another random variable

$Y$ is a Gaussian distributed random variable with zero mean and known variance: $Y\sim N(0,\sigma_y)$. We measure $Y$ with a sensor, which is corrupted by white Gaussian noise: $Z=Y+V$; $V\sim N(0,\...
Jing Zhou's user avatar
6 votes
3 answers
698 views

How to estimate the integral involving the distance function

Let $\Omega\subset\mathbb{R}^n$ be an open bounded domain with smooth boundary. Consider the following integral: $$I(t)=\int_{\Omega}e^{-\frac{d^2(y,\partial\Omega)}{t}}{\rm d}y.$$ My problem is how ...
Houa's user avatar
  • 561
-1 votes
1 answer
204 views

How to combine estimator with different variances?

Consider independent random variables $X_1,X_2,\ldots,$ that have the same expectation $\mathbb x=\mathbb E[X_1]=\mathbb E[X_2]=\ldots$ Further, assume that we know that $Var[X_i]=\sigma_i^2$. In the ...
M A's user avatar
  • 127
1 vote
0 answers
154 views

How to retrieve back the input using Bussgang theorem?

If we have a non-linear function $f$, that is applied to input $x$, we have then the output $y=f(x)$ Using Bussgang decomposition we can linearize this nonlinearity and express $y$ as $y=Bx+ η$, ...
e. sfe's user avatar
  • 39
6 votes
1 answer
433 views

Probability of complex eigenvalues

I find this is the best site to post this question, even though I considered cs. It is a Monte Carlo experiment over the set of 10.000 n×n matrices. If a single matrix eigenvalue is complex then ...
prosti's user avatar
  • 171
3 votes
0 answers
113 views

Image restoration quality general lower bounds

A typical image restoration model posits that, starting from a true image $f = f(x,y)$, we observe $$ \tilde f = f \star h + n $$ where $\star$ is convolution, $h$ is the point spread function (caused,...
Elena Yudovina's user avatar
3 votes
0 answers
265 views

Proving the exponential decay of Green's function for the lattice $-\Delta+p$

The Green function $G(x,y) =G(x-y)$ of the discrete Klein-Gordon operator $-\Delta+p$ on $\mathbb{Z}^{d}$ is given by: \begin{eqnarray} G(x-y) = \int_{[-\pi,\pi]^{d}}\frac{d^{d}k}{(2\pi)^{d}}\frac{e^{...
MathMath's user avatar
  • 1,305
1 vote
0 answers
56 views

Estimation of parameters through multivariate Taylor expansion?

I do have a function $$f(t) = \prod\limits_{j=1}^{n} \left(1 + \sum\limits_{i=1}^{n} M_{i,j} t_i\right)^{-\alpha_{j}}$$ defined by parameters: $M_{i,j} \in \mathbb{R}_{+}, \;\forall i \in 1,...,d,\; ...
lrnv's user avatar
  • 686
-1 votes
1 answer
144 views

Sufficient conditions on $ a_i,b_i$ for $a_1\phi(n)+b_1, \cdots, a_k\phi(n)+b_k$ to be simultaneously prime infinitely often?

I am really interested in sufficient conditions on $a_i, b_i$ guaranteeing that the linear forms $a_1\phi(n)+b_1,\dots, a_k\phi(n)+b_k$ become simultaneously prime for infinitely many positive ...
zeraoulia rafik's user avatar
2 votes
0 answers
385 views

Extended Kalman Filter and its State Transition Matrix

Sorry for what might be a long post, I want to give background. Initially I had regular Kalman filter, and the state model was defined by Newtonian kinematics, with initial position 0 and speed of 2. ...
retarded_Question_asker's user avatar