Questions tagged [truncation]

Truncation is a process that results in the omission of data that are beyond a threshold.

Filter by
Sorted by
Tagged with
0
votes
1answer
12 views

Partially left truncated data in bivariate time series, one series is missing data what to do?

I have two time series of futures Settlement Prices where I am to model the systematic volatility of the settlement prices for these two time series. My plan is to: Calculate the logged returns. Fit ...
0
votes
0answers
10 views

Truncation based on two variables

I have some data, which has been constructed from multiple API pulls. Observations have an expiry date, $x_i$, which means that observations which expire before the API pull is done do not appear in ...
0
votes
0answers
6 views

Expectation of truncated autoregressive process

Consider the following nonlinear autoregressive model: \begin{align*} \epsilon_t & = \epsilon^\rho_{t-1} e^{u_t}, \\ x_t & = \frac{\gamma \, \epsilon_t x^a_{t-1}}{1+b y_t}, \\ y_t & = \...
0
votes
0answers
6 views

Valid to truncate KF state estimate?

In the field I study I have come across several cases where the Kalman Filter is used together with truncating the state estimate. The most recent case is a study where the algorithm cuts the ...
2
votes
0answers
14 views

Is it Sufficient to Truncate a Left Censored Distribution?

A colleague explained their approach to dealing with left censored data in an analysis, and while I don't think it is the best approach, I am not sure if it is insufficient or not. My colleague has ...
0
votes
0answers
17 views

Dealing with zeros in the dependent variable generated by separate processes

There are several questions here on dealing with zero inflated dependent variables, but my question is slightly different than them. I am working with a continuous/count dependent variable. The ...
0
votes
0answers
38 views

Tobit model with truncated data

I would like to examine the impact of institutional ownership on M&A deal size, as in Andriosopoulos & Yang (2015). However, I am in doubt which regression method to use for measuring this ...
1
vote
0answers
28 views

Understanding left-truncated data in survival analysis

I am having a hard time grasping the concept of left truncation. According to what I understand, left truncation occurs when we observe individuals only if their event of interest takes place after ...
2
votes
1answer
23 views

How do we obtain the probability density of a truncated regression with an upper and lower bound

I know my density for $y$ is supposed to be something of this form $$g(y|x_{i},t)=\frac{f(y|x'\beta, \sigma^{2})}{F(t|x' \beta' \sigma^{2}}$$ where the numerator is the density of the normal ...
0
votes
0answers
11 views

Estimation of beta and sigma for a model truncated from above and below

The following model is truncated from above and below Y = x′β + e ,if L < Y* < U not observed if otherwise How do we show the estimation of β and σ2 using MLE by deriving the Log-...
0
votes
1answer
25 views

How to handle truncated or missing ranking data in a classification problem?

I'm preparing data for a classification problem that involves matches in a single-player sport. In each match, each competitor is either ranked and thus has a numeric rank; or unranked (rare but can ...
0
votes
0answers
40 views

Angle of Line in a non-Normal Q-Q Plot

I'm currently working on a toy-problem of $n=15$ data-points and believe that my data may have come from a Truncated Normal Distribution with a lower-bound of $a=5.0$. I'm using the R's ...
2
votes
2answers
145 views

Moments of truncated Student's $t$-distribution

I performed random sampling on a Student's $t$-distribution. I used SciPy to calibrate my parameters and then truncated my allowable values to the maximum and minimum observation in the data for ...
0
votes
0answers
40 views

Truncation versus censoring with Kaplan-Meier

I am trying to run Kaplan-Meier on a rather odd dataset and am having difficulty determining whether I should be truncating or censoring my data. I have looked at the other feeds, including this very ...
2
votes
1answer
119 views

Fitting a gamma distribution to truncated data

I am faced with the following truncation problem: $$ X_i \sim \Gamma(\alpha, \beta) \\ \delta_i = \chi(X_i \le \tau_i) $$ I can observe only $(X_i, \tau_i)$ where $\delta_i = 1$ and I have no a-...
2
votes
1answer
40 views

What is a sensible way to truncate data to a region that fits a model?

I want to use an exponential decay model in python to relate the flow rate in a device to the mass left inside it, in particular $flow=a−b×e^{−c×mass}$ where a, b and c are the parameters of the model....
4
votes
2answers
190 views

Distributions with simple truncated expectations

For a project I'm looking for continuous distributions which have a somewhat simple closed form for upper-truncation expectation ($E[x|x>c]$). Here are two examples I've found so far: Exponential ...
0
votes
0answers
34 views

Truncation of distance matrix

Given a sample $\textbf{X}_1$,...,$\textbf{X}_n\in\mathbb{R}^p$ from an arbitrary distribution with distribution function $F$ we can calculate the pairwise Mahalanobis distances between the sample ...
3
votes
1answer
60 views

How do to deal with data missing NOT at random?

It seems that because values are missing from a specific range of my target variable, my model performs poorly when predicting samples that are actually in that range. My target variable is ...
1
vote
0answers
48 views

Estimate population variance / mean from truncated distribution with known cutoff, but without parametric assumptions

Suppose you have a sample of $N$ iid random variables $X_i$ drawn from an unknown (but finite variance) distribution but with a known upper-cutoff $K$ and therefore support $[0,1,2,...,K]$ but un-...
0
votes
0answers
150 views

Right truncation and right censoring

Is is possible for a survival data to be **right truncated and right censored **. If so, please leave an example for better understanding. Thanks in advance!
0
votes
0answers
53 views

Right censored or right truncation and Cox model?

Suppose, a list of targeted population is invited to participate in a health program. Invitation date could vary for every individual based on eligible criteria (this criterion is the same for all). ...
1
vote
1answer
28 views

Can sampling from a truncation of a random variable, rather than the original variable be more Blackwell-informative?

Suppose you are interested in finding the mean of a random variable. You have some prior belief of it and before sampling 1 observation, you can decide whether to sample from the original random ...
6
votes
2answers
1k views

Compute truncated normal distribution with specific mean and variance

I have a simple setting: I simulate demand patterns that are distributed according to a truncated normal distribution with a given mean and variance after truncation. The truncation is from the left ...
1
vote
0answers
85 views

Survival analysis: how to account for immortal time with time-dependent exposure

I am working on a survival analysis to look at time to preterm birth (birth before 37 weeks). I have a time-dependent exposure that can occur anytime at or after 28 weeks, defined using a heaviside ...
0
votes
0answers
68 views

Working out the true mean of a distribution from a truncated set of observations

Suppose people receive a random draw which represents the probability of some event. The draws are taken randomly from a normal distribution with true mean $\mu$ and standard deviation $\sigma$. ...
7
votes
1answer
2k views

Distribution of sum of independent exponentials with random number of summands

Let $\tau_i\sim\exp\left(\lambda\right)$ be independent and identically distributed exponentials with parameter $\lambda$. Then, for given $n$, the sum of these values $$T_n := \sum_{i=0}^n \tau_i$$ ...
1
vote
0answers
41 views

Truncated count model — including information about the number of unobserved realisations

Background Suppose we have a model such that $Y \sim \mathcal{M}(\theta)$ is a discrete random variable taking values in $[0, 1, \ldots]$. We would like to make inference about $\theta$ from a ...
6
votes
2answers
404 views

Efficient random generation from truncated Laplace distribution

We have several ways of drawing random samples from Laplace distribution. Is there any efficient way of sampling from left truncated Laplace distribution? Inverse transform sampling is an obvious ...
1
vote
0answers
35 views

Can I consider this as a truncated normal distribution?

I have a variable whose maximum value is fixed (maximum number of days in the observation period). In some plots, the histogram of the log-transformed variable peaks near the maximum, but not at the ...
-1
votes
1answer
407 views

How to model left-censored and right-truncated data on Stata? [closed]

I have data that is left-censored and right-truncated. I'd like to run a tobit or truncreg. Although, using ...
1
vote
2answers
190 views

Survival in two period game: mean of z|z<v with z=xy, x~U(a,b) and y~U(c,d)

I am looking for the functional form to describe the following: A random shock $x\sim Uniform(a,b)$ is multiplied with a second shock $y\sim Uniform(c,d)$. What is the mean value of all combined ...
2
votes
0answers
308 views

Truncated mulitvariate normal: first two moments

Let $X\in \mathbb{R}$ be a univariate random varible for which it holds that $$ X \sim N(\mu,\sigma^2).$$ where $\mu\in \mathbb{R}$ gives the expected value and $\sigma^2>0$ is the variance. If ...
0
votes
0answers
54 views

What does a truncated distribution mean? [duplicate]

I am a little bit confused about truncated distributions such as truncated normal distribution. I have a code in FORTRAN where the function gen_rnorm(mean,sigma) ...
3
votes
1answer
365 views

Truncated probit regression

I have a particular situation. I would like to build a probit model to predict a given outcome $Y=\{0,1\}$ based on a set of predictors $X$. A probit model has the form: $$\text{Pr}(Y=1\,|\,X)=\Phi(...
5
votes
2answers
957 views

Mean vs. Trimmed mean in the normal distribution

In a simple experiment with the normal distribution in R I ran 500 iterations of a simulated normal distribution with N=100 each. For each iteration from the 500 iterations, I calculated both the ...
1
vote
0answers
86 views

Right, Left, Interval, Delayed, and truncted data

I have a medical data set that has all the following cases: Right-censored Left-censored ...
4
votes
1answer
201 views

Expectation of $X$ given $X < c$

Let $X$ be a random variable with PDF $f(\cdot)$ and CDF $\Phi(\cdot)$. I want to compute $E(X \mid X < c)$, where $c$ is some constant. Using definition of the expected value $$E(X \mid X < ...
2
votes
1answer
699 views

Poisson distribution where x is at least 1

Is this as simple as saying that the probability that x equals zero is $e^{-λ}$, so the probability that x is 1,2,..... is $1-e^{-λ}$, so we just divide the usual pmf for poisson distribution by the ...
7
votes
1answer
1k views

How to calculate a partial expected value of beta distribution (mean of a truncated beta)?

Given a Beta Distribution with a=2, b=3, we can find an expected value (mean) for the interval [0, 1] = a/(a+b) = 2/5 = 0.4 and median = (a - 1/3)/(a+b-2/3) = 0.39, which are close. I am looking for a ...
0
votes
0answers
297 views

Hypothesis test for truncated distributed random variables in Bayesian Regression

As per the recommendation, I am re-framing my questions. I am doing a Bayesian Regression where the parameters are truncated at zero ($0< \beta < \infty$, Assuming prior to follow truncated ...
1
vote
1answer
99 views

Modeling potentially unimodal data

My data: I surveyed for animal densities across an elevation gradient. Let's say I surveyed from 0 to 1000 meters elevation. My models (one for each species of interest): density ~ elevation + other ...
0
votes
1answer
517 views

Weibull Regression of Left Truncated Data in R

I have a data set of tree diameters that do not include any measurements below a 7.5 due to the difficulty in identifying species when they are small. I want to run a Weibull regression that returns ...
2
votes
1answer
437 views

Definition of Zero-truncated Poisson distribution

The definition of zero-truncated Poisson (ZTP) distribution is: \begin{align} g(k;\lambda)= P(X = k | X > 0) &= \frac{f(k;\lambda)}{1-f(0;\lambda)} \\[8pt] &...
3
votes
3answers
1k views

Right-Truncated Survival Analysis

I'm working on a survival analysis in R using the survival package - and I am wondering what modifications I need to account for when using right-truncated data (which I think is what I have) (there ...
3
votes
0answers
77 views

Swiss Cheese Distributions

I am curious about a normal distribution with no probability mass in certain regions, sort of like the complement of the truncated normal. In particular, it will have zero mass in a circular region. ...
1
vote
0answers
410 views

Do I have Left Truncation or Right Censoring in my Survival/Event History Analysis?

I am doing study that starts at a specific date, January 1st 2015, and ends on a specific date, December 31st 2015. My overarching research question revolves around modeling time between orders of ...
-1
votes
1answer
28 views

Would there exist a symmetry around the mode in a truncated uni-modal distribution (which is differentiable)?

If we truncated around the mode of an asymmetric (continuous and differentiable) unimodal distribution, would there be a symmetry around the truncation point? For example if X is generated from an ...
10
votes
2answers
2k views

Efficiently sampling a thresholded Beta distribution

How should I efficiently sample from the following distribution? $$ x \sim B(\alpha, \beta),\space x > k $$ If $k$ is not too big then rejection sampling may be the best approach, but I am not ...
3
votes
1answer
588 views

A truncated exponential distribution is surely not an exponential distriution?

I'm currently working through a set of old past exam papers for a course, and came across this question which just has me flummoxed. I've slightly rephrased the relevant information and the question ...