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1
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0answers
25 views

Regression method if dependent variable is the absolute value of a continous variable [duplicate]

Suppose we have a dependent variable $Y$ that has normal distribution with a mean of $0$. If I run a regression model using the absolute value of $Y$, $|Y|$, i.e. $|Y| = b_1 + b_2 X + u$, my dependent ...
2
votes
0answers
23 views

Unbiased Estimator of the truncation points in a truncated normal distribution?

Consider the variables $x_i \text{~} \mathcal{N}(\mu, \sigma^2,a,b)$ iid with truncation points $a$ and $b$, i.e. $a < x_i < b$. Suppose all 4 parameters, namely $\mu, \sigma, a, b$ are all ...
4
votes
1answer
63 views

How to derive the mean and variance of a $k$-truncated Poisson?

How can I derive the mean and variance of a $k$-truncated Poisson? Here, $k$ is the cutoff value such that only values strictly larger than $k$ are allowed, i.e. the probability mass function is ...
0
votes
0answers
38 views

Mean of a truncated quadratic function of a normal variable

Suppose you want to compute the mean of the following random variable: $$ V=\left(\frac{z-y}{z}\right)I\left(y<z\right)-\left(\frac{z-b_0}{z}\right)I\left(b_0<z\right) $$ where: $$ ...
2
votes
0answers
54 views

Truncated power basis function and continuity in b-splines

I do not understand how adding a truncated power basis function leads to continuity in B-Splines. Could someone please provide a low level explanation?
1
vote
2answers
43 views

Appropriate priors for truncated regression model

I have a simple linear regression model with the constraint that my dependent variable y (response time) has to be greater than zero. I want to specify priors for intercept, slope and sigma (the ...
2
votes
1answer
92 views

Creating a probability distribution that is truncated skewed

I have a dataset I want to use to generate a probability distribution. The distribution is skewed and can only include positive integers. I've tried normal (both skewed and truncated, although I ...
4
votes
0answers
41 views

Truncated trivariate normal - conditional expectation

I am working on a paper in which I'd need to use the two following conditional expectations: $E(X_{1}|a \leq X_{2} \leq b)$ $E(X_{1}|a \leq X_{2} \leq b, a \leq X_{3} \leq b)$ where $X_{1}, X_{2}, ...
1
vote
0answers
28 views

Conditional moments of bivariate normal

Suppose that (X,Y) are bivariate normal with non-zero means and correlation. Is there any neat expression for $\mathbb{E}(X|Y>0)$?
2
votes
0answers
56 views

Proving a “well-known” result regarding the distribution of a normally distributed random variable

In an important project work, I would like to include a "proof" of the following, but have unfortunately been unable to readily compute it myself. I am aware that this is a flaw on my part, but ...
1
vote
0answers
47 views

Regression with dependent variable which ranges from -1 to 1

I performed a series of Pearson correlations which give me as expected values between -1 and 1 (actually very few below zero). I'd like now to see if some factors are linked to these correlation ...
1
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0answers
41 views

The most general definition of the Likelihood function for continuous data (including truncation and censoring)

How would you rigorously define the likelihood function for censored/truncated observations? Even in most lifetime/reliability literature (where these types of observations are frequently encountered) ...
0
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0answers
38 views

Conditional expectation in mixture distributions

I have a mixture distribution for observed lifetime data $(\delta_i,t_i,L_i)$, where $\delta_i$ is a censoring variable (1 indicating death, and 0 indicating censoring), $t_i$ is the observed lifetime ...
18
votes
2answers
4k views

What is the difference between censoring and truncation?

In the book Statistical Models and Methods for Lifetime Data , it is written : Censoring: When an observation is incomplete due to some random cause. Truncation: When the incomplete nature of ...
5
votes
2answers
532 views

How should I model a continuous dependent variable in the $[0, \infty]$ range?

I have a dependent variable that can range from 0 to infinity, with 0s actually being correct observations. I understand censoring and Tobit models only apply when the actual value of $Y$ is partially ...
1
vote
0answers
529 views

Two-part models in R: continuous outcome with too many zeros

I am estimating a model where the outcome variable is continuous, more specifically a percentage in the form of a 0 to 1 range. This variable has one potential problem: many of its cases equal zero ...
1
vote
1answer
35 views

Correlation with one variable missing half of its values

Let´s say I want to run a correlation between "eye spherical defect" and height and I want to use only individuals with myopia, whose "spherical defect" goes from 0 to -20 or so. Whereas the ...
3
votes
3answers
469 views

Intepretation of Kaplan Meier with truncated and right censored data

I cannot seem to understand the interpretation of the Kaplan-Meier with truncated data. Here, we have associated, with the j:th individual, a random age $L_j$ at which he/she enters the study ...
3
votes
0answers
291 views

Is there a way to model left truncated and interval censored data in R or SAS?

We have a study where our participant underwent some surgery at time = 0, but at various ages. Our follow-up is based only on Medicare age-eligible people, so we have to wait until they reach the age ...
2
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0answers
43 views

proper one-sided test for truncated distribution

I have positional segments that contain N number of mutations. Each mutation has a frequency which is determined by taking the number of reads supporting the alternate allele (r) and dividing them by ...
3
votes
0answers
93 views

Estimating parameters in a truncated binomial distr

I would like to find the estimates of the parameters in a truncated (at zero) negative binomial distribution.Suppose $Z$ has this distribution with parameters ($\alpha,\beta$). (The parametrization ...
1
vote
1answer
107 views

Obtaining the Log-logistic distribution from a truncated logistic distribution

Let $$f(x) = \frac{e^x}{(1+e^x)^2}~,~ -\infty \lt x \lt \infty~~~~~(1)$$ be the standard logistic pdf of a random variable $X$. Then one can obtain the pdf of the log-logistic distribution via the ...
0
votes
1answer
84 views

Sum of truncated normal distributions with other distributions (like uniform) that have partially common domains

I have some truncated normal distributions and some other distributions (like uniform distribution) that have partially common domains. I'd like to know how can I calculate the entropy for the sum of ...
2
votes
0answers
42 views

Clarify terminology regarding truncated and censored distributions [duplicate]

I'm looking for clarification on the definition of truncated distributions and on terminology for censored distributions and truncated distributions. I recently had a [dialog on SO][1] regarding [a ...
0
votes
2answers
102 views

Calculating $\overline{X}$ and $S(X)$ for a truncated Normal distribution

I have the following dataset which appears to be normally distributed but is truncated at 0. If I ignore the values which are 0 I get an even better distribituion. I would like to conclude that ...
0
votes
1answer
237 views

Censored data from a truncated distribution (Stan)

I'm trying to write a survival model of fossil species durations. In this case, the minimal possible duration for a species is 1. Also, the general idea in paleontology is that we are only observing a ...
3
votes
1answer
187 views

Folded Normal and truncated Normal

Suppose to have a vector of random variables $\mathbf{y}$, distributed as a multivariate normal with mean vector $\boldsymbol{\mu}$ and covariance matrix $\boldsymbol{\Sigma}$. The variable ...
0
votes
1answer
44 views

Running regressions on subsamples: Include the variable on which the subsample is based in the regressions?

Income is one of my independent variables in a sample of 2000 households. I'd like split the sample along household income lines (poor, vulnerable and non-poor). Is there a reason not to include ...
3
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0answers
254 views

Truncated Gamma distribution parameter estimation

I need to estimate the parameter of a Gamma distribution form the data, but I only have samples from 0.05 to 3 (most of the samples are concentrated here). I tried MLE but due to the truncation is ...
1
vote
0answers
18 views

error on truncated rms

I am computing the RMS of a sample to estimate the standar error $\sigma$ of the underlying distribution (for simplicity let say a normal distribution $N[\mu$, $\sigma$]). $ \text{RMS} = \sum_{i=1}^N ...
1
vote
1answer
51 views

Area under a truncated distribution = 1

I have computed a truncated normal distribution, which total probability density (i.e. area under the curve) is equal to 0.92. The distribution represents well the reality of the phenomenon I am ...
4
votes
2answers
1k views

Survival analysis in R with left-truncated data

I am doing a survival analysis in R with the survival package. I think I am working with left-truncated data, but I'm not entirely sure how to handle it. I have a ...
8
votes
2answers
278 views

Sum of normal truncated random variables

Suppose I have $n$ independent normal random variables $$X_1 \sim \mathrm{N}(\mu_1, \sigma_1^2)\\X_2 \sim \mathrm{N}(\mu_2, \sigma_2^2)\\\vdots\\X_n \sim \mathrm{N}(\mu_n, \sigma_n^2)$$ and ...
2
votes
0answers
64 views

Truncated normal in WinBUGS

I want to use the following truncated normal distribution in WinBUGS to estimate parameters of SEM using Bayesian analysis. ...
3
votes
1answer
92 views

How can I estimate the tail of a distribution with a truncated distribution?

The broadband speed data I'm working with have all values over 30Mbps placed into a >30 category. The distribution is thus truncated. This leads to the final column in the histogram below being a ...
1
vote
1answer
331 views

Expectation of Truncated & Random Variable

I have what appears to be a relatively simple question, but am struggling to understand how to go about answering it. The general question is as follows: What is the expected value of $S_{I}$, ...
1
vote
0answers
112 views

Is it possible to model BOTH censoring and truncation in BUGS?

Survival times are often right censored and left truncated. From my experience, it does not seem like OpenBUGS allows for both. Truncation is denoted as T( , ) and censoring as C( ,). For instance, a ...
2
votes
2answers
143 views

Appropriate distribution for bounded data set

I am designing a points-scored test. There is a limit on the maximum amount of points possible, as well as on the fewest amount of points possible. I have had a test group take the test and graphed ...
14
votes
4answers
7k views

What are the relative merits of Winsorizing vs. Trimming data?

Winsorizing data means to replace the extreme values of a data set with a certain percentile value from each end, while Trimming or Truncating involves removing those extreme values. I always see ...
2
votes
1answer
145 views

Way to correct sample selection bias with unknown selection?

I would greatly appreciate some advise on a statistical problem that haunts me. Suppose you wish to estimate the effect of $x$ on $y$, but the probability to observe $\{y_i, x_i\}$ also depends on ...
1
vote
0answers
106 views

Error of data fitting by gamma.fit() in Python

I need to find gamma fit for data in Python 3.2. param = gamma.fit(samp) // samp is a list of floating point numbers I got error: ...
1
vote
0answers
129 views

General truncated Poisson distribution: R routines

I face an applicaton with (a possible) five-truncated Poisson distribution - I count periods at least five days long, thus data of the type (5, 8, 12, 5, 5, 10, ...). Much theory and software is ...
2
votes
1answer
144 views

Can we still use OLS on truncated a $Y$ if its conditional distribution is normal?

I was recently reading about Heckman selection models, and got sidetracked by how little I knew about truncated data. I was reading these slides, and on page 78 Baum mentions that if part of a sample ...
0
votes
1answer
225 views

Joint distribution of a Normal and Truncated Normal

I have a random variable $X\sim \text{Normal}(\mu,\sigma)$ and have the transformation $Y=\max\{0,X\}$. Is the distribution of $Y$ a truncated normal where it is truncated to live on the positive ...
1
vote
2answers
118 views

Response variable bounded by dependent variable

I have a problem: y~x1+x2+x3+x4 where the response variable y is always more than or equal to the explanatory variable x1 (for e.g. x1 represents the income of one person in a couple and y is the ...
3
votes
0answers
135 views

Truncated Explanatory Variable

I am running a model where one of the explanatory variables is truncated. In particular, the variable measures the duration of unemployment (retrospectively) in months and it is truncated at 2 years, ...
2
votes
1answer
64 views

$E(x^k)$ under truncated $\mathcal{N}(\mu,1)$

There is a similar question in $E(x^k)$ under a Gaussian. However, it doesn't seem to be trivial when $\mu\ne0$. As mentioned in the previous question $k$ is not an integer. The integral that I need ...
3
votes
1answer
78 views

Joint probability of two correlated RVs

I am trying to get the joint PDF of two RVs $X$ and $Y$ where $aX<Y<bX$, so I am stuck in calculating the probability of $\mathbb{P}(X<x,Y<y|aX<Y<bX)$ any idea?
2
votes
1answer
1k views

How do I use the “survival” package and “Surv” function in R with left-truncated data?

I am trying to run survival analysis using the Surv and survfit functions from the survival ...
3
votes
2answers
225 views

Calculation of an “unconstrained” normal distribution (starting from a censored one)

Assume that two r.v. $W$ and $Y|W=w$ with (1) $W \sim \text{N}(\mu_w,\sigma_w^2)$ (iid) (2) $Y|W=w \sim \text{N}(w,\sigma_y^2)$ (iid) Further we only observe $Y$ if $Y$ is less then $W$, i.e., ...