Skip to main content

Questions tagged [conditional]

This tag is ambiguous. Consider replacing it with a more specific tag such as [conditional-probability], [conditional-expectation], [conditional-random-field] or [conditional-independence].

Filter by
Sorted by
Tagged with
0 votes
0 answers
11 views

How does conditional logit deal with binary predictors in choice sets of three or more alternatives?

I am interested in clogit, not multinomial logit, and the overall effect of the predictor on the choice of n alternatives that can only be identified by their attributes (i.e., the choice sets are ...
Olifa's user avatar
  • 1
0 votes
0 answers
8 views

Adjustment in DLNM - case control setting

I have data in a case-control format with a 5-year lag of exposure. I want to adjust, in addition to the strata, for the number of monitoring stations used to calculate the exposure. The problem is ...
Nitzan Sagie's user avatar
0 votes
1 answer
27 views

How to calculate the statistic for ctree function?

...
Apai's user avatar
  • 19
0 votes
0 answers
28 views

Distribution of conditional independence

I have random variables W,A,Z,U and know that the following conditional independence holds: $W \perp (A,Z)|U$. Is it correct to then state that $W|ZA\sim W|U$? My reasoning is the following but am ...
MarsRooover's user avatar
0 votes
2 answers
33 views

Statistical significance for high values of IV

I (beginner…) need some general guidance on regression analysis: I have run an OLS regression on some data and I’ve had some statistically significant relationships between IVs and the DV. My ...
sant's user avatar
  • 1
0 votes
0 answers
24 views

Reference datasets for conditional density estimation

[In case you feel inclined to close this question because I'm asking for a dataset - I'm looking for solutions in the spirit of point 2 (on-topic) in the accepted answer to this question about asking ...
Scriddie's user avatar
  • 2,429
0 votes
0 answers
21 views

Prediction Machines Word Problem (Conditional Probability?)

I am new to statistics but had what I think is a pretty simple question: Prediction machine 1 correctly guesses the outcome of binary (yes/no) events 60.4% of the time. Prediction machine 2 correctly ...
Eigeas's user avatar
  • 1
0 votes
1 answer
33 views

Prove that the equality holds [closed]

How to prove that for any random variables $X$, $Y$ and $Z$ with finite variances, we have $Cov(X,Y)=E(Cov(X,Y|Z))+Cov(E(X|Z),E(Y|Z))$?
Amirhossein's user avatar
0 votes
0 answers
43 views

Posterior of Inverse Wishart distribution with a subset of data observed

Suppose: \begin{equation} x_1\in \mathbb{R}^{p_1}\\ x_2\in \mathbb{R}^{p_2} \end{equation} such that \begin{equation} x \sim \mathcal{N}( \begin{bmatrix} x_1\\ x_2 \end{bmatrix}; \begin{bmatrix} \...
Snowy Baboon's user avatar
0 votes
0 answers
36 views

How to prove that $P(\pi_2 \mid \pi_1)=P\left(\mathbf{X} \in R_2 \mid \pi_1\right)=\int_{R_2=\Omega-R_1} f_1(\mathbf{x}) \,d \mathbf{x}$?

Let $f_1(\mathbf{x})$ and $f_2(\mathbf{x})$ be the probability density functions associated with the $p \times 1$ vector random variable $\mathbf{X}$ for the populations $\pi_1$ and $\pi_2$, ...
Ahad Dehghani's user avatar
0 votes
0 answers
24 views

Bridging the gap from theory to implementation in "Conditional Distance Correlation" by Wang et al. 2015?

In an attempt to implement a form of conditional distance correlation for random variables represented as vectors of observations, I came upon this paper that nicely extends the notion of distance ...
QMath's user avatar
  • 451
-1 votes
1 answer
77 views

difference between two sets of pvalues

I am performing a biological experiment, where I am trying to capture potential mediation effects from some genes. I have 150 significant results, containing 30 tissues with different sample size. For ...
dsbo's user avatar
  • 11
1 vote
0 answers
103 views

Given a DAG X<-Z->Y, how to test for conditional independence of X and Y given Z for non-normal random variables?

Consider data generated from a directed acyclic graph (DAG) of the form X<-Z->Y. Based on d-separation of DAGs, X is independent of Y given Z: X_||_Y|Z. If X, Y and Z are multivariate normal, ...
Bill Shipley's user avatar
0 votes
0 answers
27 views

Reformulating latent dirichlet allocation

can you guys help me solve this equation and go from : to this one : I have tried something but my result gives me this : p(θ, φ, z| α, β) = p(θ, φ, z, w|α, β)/p(w|α, β) the equations are taken from ...
Meyssan's user avatar
1 vote
0 answers
58 views

Binomial distribution conditional on the weigthed sum?

Suppose $\mathbf{X}$ is a vector of iid Bernoulli variables with the fixed success probability of $p$. The variance of X is $np(1-p)$. Now, suppose, I am interested in the conditional probability of $...
entropy's user avatar
  • 19
2 votes
1 answer
60 views

are there any conditions on the data in ANN classification?

In regression models such as linear and multiple regression models, there are several conditions that must be met such as normality, non-autocorrelation, heteroscedasticity etc. does ANN also have ...
andryan86's user avatar
  • 127
4 votes
2 answers
581 views

Can we estimate ATE (average treatment effect at the population level) using both marginal or conditional models?

If I understood correctly, in principle when we estimate an unconditional/unadjusted treatment effect, it means marginal effect and vice-versa. If so, I wonder if the average treatment effect (ATE) at ...
user332276's user avatar
2 votes
1 answer
205 views

Conditional probability - Finding a lost dog on the second, but not first day of a search

I am working on problem set 2, Q4d from the MIT 6.041 Oscar has lost his dog in either forest A (with a priori probability 0.4) or in forest B (with a priori probability 0.6). On any given day, if ...
Joseph's user avatar
  • 143
1 vote
1 answer
120 views

Marginal predictions from a conditional survival model

I’m looking at making predictions of baseline and treated survival from a parametric survival curve that are unbiased. I have a matched sample to try to control for observed confounding and wanted to ...
Geoff's user avatar
  • 741
1 vote
0 answers
125 views

Efficient estimation of conditional probability density

The formulation of the conditional density is: $$ f_{Y|X}(y|x) = \frac{f_{X,Y}(x,y)}{f_X(x)}. $$ I need to estimate this density from data and it's prohibitively time-consuming to calculate the joint ...
smthack's user avatar
  • 61
1 vote
3 answers
149 views

A stick of length 1 is split at a random position $B\sim U(0, 1)$. Let $X$ be the length of the longer stick. What is the PDF of $X$?

A stick of length 1 is split at a random position $B$ where $B$ ~ $U(0, 1)$. Let $X$ be the length of the longer stick. What is the CDF of $X$? This problem is challenging me. I know that the cdf of X ...
Franklin V's user avatar
1 vote
2 answers
322 views

Conditional Logistic Regression?

Firstly, I am new to all of this. I am currently trying to predict the chance of different students finishing top of their class. Students will be separated into different groups depending on the ...
CRJH's user avatar
  • 13
1 vote
1 answer
93 views

Pre- and post-treatment binary outcome between treatment groups

I have two treatment groups (A and B), where I have a binary outcome of resistance against a particular antibiotic recorded at pre- and post-treatment. I am interesting in determining whether there is ...
Jack's user avatar
  • 11
8 votes
3 answers
2k views

Difference between E(Y) and E(Y|X) in regression

In linear regression, we postulate a model for estimating $E(Y|X)= \beta_0 + \beta_1 x$ We also propose $Y= \beta_0 + \beta_1 x + \mu$ where μ is an error team with expectation equal to zero. We also ...
Agustín Cugno's user avatar
0 votes
0 answers
106 views

Use indicator function in regression equation

I have 2 regression equations: 1st Regression: $I_t = a_1 + \beta_1E_t+X'_t\delta_1+\epsilon_1$ 2nd Regression: $I_t = a_2 + \beta_2E_t+X'_t\delta_2+Y'_t\lambda_2+\epsilon_2$ The two regressions are ...
miamialan's user avatar
4 votes
3 answers
461 views

Can I say that $E[X | c] = E[c | X]$, when $c$ is a constant and $X$ is a random variable?

$X$ is a random variable defined in a sample space $c$ is a constant $\in R$ (real numbers).
Raffaela's user avatar
0 votes
2 answers
76 views

Conditional count based on second variable

I'm still somewhat new to R, so please bear with me. I'm trying to summarize the results of the variable riskT0. However, because I have some missing values in the variable riskT2 I would like to ...
Blubbb's user avatar
  • 15
1 vote
2 answers
219 views

Multiple correlation formula

Given $v \sim N_{p+1}(\mu, \Sigma), v = (x, y)', \mu = (\mu_x, \mu_y)', \Sigma = \begin{pmatrix} \Sigma_{xx} & \sigma_{xy} \\ \sigma_{yx} & \sigma_{yy} \end{pmatrix}$, how do you prove the ...
tintinnabulum's user avatar
0 votes
0 answers
35 views

Given a Poisson distribution Poisson(n│λ) with expected value λ, which integer n is the most probable one? [duplicate]

Given a Poisson distribution Poisson(n│λ) with expected value λ, which integer n is the most probable one? Prove that, if 𝜆 is integer, there are two most probable values for 𝑛.
David's user avatar
  • 1
3 votes
1 answer
113 views

Implications of mean independence

Let $U$ be a random variable with mean $0$. Take other two random variables $X,Y$. Assume $$ (1)\quad E(U|X,Y)=0. $$ I believe (1) implies $$ E(U\cdot X)=E(U \cdot Y)=0. $$ Does (1) imply $$ E(U \cdot ...
Star's user avatar
  • 861
1 vote
1 answer
43 views

A Condition a Conditional Probability Should Satisfy

Consider four random variables $V_1,V_2,V_3, V_4$. Here, suppose that $V_2$ is a function of $V_3$ and $V_4$, say $V_2=V_3-V_4$. In this case, I want to know whether the following conditional ...
M.C. Park's user avatar
  • 935
2 votes
0 answers
45 views

Quick short question about understanding of conditional expectation [duplicate]

let me just ask one simple question, I am not sure if I understand this concept of conditioning w.r.t. sub-$\sigma$-algebras. Let $(\Omega,\mathcal{A},\mathbb{P})$ be probability space and $X,Y:\Omega\...
MatEZ's user avatar
  • 81
1 vote
1 answer
316 views

Condition on two random variables

I'm trying to set up the proper assumptions for a proof I'm working on: Given that $P(A|e) = P(A)$ and $P(A|c,e) = P(A|e)$, can we prove that $P(A|c)=P(A)$? I understand that A is independent of e and ...
Kevin D's user avatar
  • 13
2 votes
1 answer
963 views

is P(notB|A) same as not(P(B|A)) [closed]

is P(notB|A) same as not(P(B|A)) if not then what is the difference between them? this is taken from bayes question.
abd m's user avatar
  • 37
1 vote
0 answers
18 views

how do i empirically estimate variance of conditional normal distribution?

I've tried searching for this, but maybe I'm not using the correct search strings. suppose I have joint distribution $P(X_1,X_2)$ over 2 continuous random variables $X_1,X_2$ that I can sample from. ...
user3246971's user avatar
0 votes
0 answers
121 views

CAPM Estimation

Please that might sound basic for all of you but I am not an expert and I need to estimate the following model using OLS regression: R= a + β1 RM + β2(z)RM + ε (the model is called conditional CAPM, ...
Sima's user avatar
  • 11
1 vote
0 answers
255 views

The discriminator is classifying everything as fake. What does it mean?

I am using a conditional GAN with a relativistic loss function for both generator and discriminator (https://arxiv.org/abs/1807.00734). Before I added the relativistic part, the discriminator ...
Rima's user avatar
  • 11
1 vote
1 answer
186 views

conditional quantile and conditional expectation

I was reading some papers and I found some parts are tricky to understand. Assume I have price data , what does it mean to calculate the conditional mean of the price data given yesterday price ? ...
A.F.R.S2022's user avatar
1 vote
0 answers
25 views

mean and covarince matrix of AR(1) [closed]

assume I have a price data called pt, I fitted AR(1) model p_t= alpha + beta pt_1 + e_t , ...
A.F.R.S2022's user avatar
3 votes
1 answer
819 views

Are exact logistic regression and conditional logistic regression the same?

I have seen these two terms in practice. Are they actually referring to the same method? If not, what is the main difference between the two methods? Conditional logistic regression is commonly used ...
hehe's user avatar
  • 743
0 votes
2 answers
55 views

Conditional probability to be calculated but I'm not able to solve the first part of the question [closed]

Suppose that a box contains one blue card and four red cards. The red cards are labelled $X$, $Y$ , $Z$, and $W$. Suppose also that two of these five cards are selected at random, without replacement. ...
Nikhil Rattan's user avatar
1 vote
1 answer
26 views

Conditionalizing events on more than one event

I am currently working on a question which seems to have an obvious answer, but it it seems just impossible for me to find a stringent proof of this relation (if it is true). Imagine the following ...
Zito's user avatar
  • 11
0 votes
1 answer
51 views

Conditional mutual information

I have three RVs X, Y, and T. Is the following equation true? I(X ; Y|T) = I(Y ; X|T) Can we express the conditional mutual information as: (X;Y|T) = I(X;Y) - I(X;Y;T) ?
nivedita's user avatar
0 votes
1 answer
389 views

Is there a way to think about conditional vs unconditional heteroskedasticity graphically?

I find I understand concepts much better with the aid of charts/visualizations. I'm struggling to intuitively understand how one would be able to see whether error terms are correlated or not to the ...
levered_up's user avatar
0 votes
1 answer
206 views

marginal and conditional distributions

Can someone help me, please? Let X and Y be two random variables having the following marginal and conditional distributions. 𝑌|𝜇 ~ 𝑃𝑜𝑖(𝜇) 𝜇 ~ 𝐺𝑎𝑚𝑚𝑎(𝛼, 𝛽) I want to obtain the ...
Fırat Çeven's user avatar
1 vote
0 answers
116 views

combinatorics questions from coursera [closed]

Question 1 Imagine that now host have the following instructions. Put a prize behind a random door. Let the guest guess a door. If the guest chooses an incorrect door (with no prize), roll a dice (in ...
revathi's user avatar
  • 11
1 vote
1 answer
256 views

"Automatically" detect biased subsets in probability distribution

Background: Suppose we have a model generating probabilities conditional on a state vector - for simplicity we can just assume the outcome is 0 or 1 (imagine for example simple logistic regression): $...
Christian's user avatar
1 vote
1 answer
248 views

How to compute conditional mean in GLM?

I have understood the basic knowledge of GLM. I know why a GLM consist of a predictor, a link function and a distribution. But I don't know how does the conditional mean connect to the distribution. ...
Stanley Chan's user avatar
0 votes
1 answer
88 views

How to solve the probability of N events occurring at the same time, N is a random variable [closed]

How to solve the probability of N events occurring at the same time, N is a random variable and its PDF is known. The probability of each event is also known and the probability of each event is not ...
Kenn Tie's user avatar
1 vote
0 answers
29 views

Conditional distribution of Yt, non-Gaussian linear growth model (time series)

Given the following modelling specifications: $Y_t = µ_t + σ_ee_t, \quad e_t ∼ t_1$ $µ_t = µ_{t−1} + β_{t−1} + w_t, \quad w_t ∼ N(0, σ^2_w)$ $β_t = β_{t−1} + v_t, \quad v_t ∼ N(0, σ^2_v)$ What is the ...
username97's user avatar