Questions tagged [deterministic]
The deterministic tag has no usage guidance.
29
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110 views
Frequentist vs Bayesian and deterministic vs stochastic [closed]
So this is sort of a general/basic, likely dumb question. I'm hoping to get a general idea, to better guide what I search/read. How do these terms relate to each other. I know with Bayesian theory, ...
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40 views
Is hierarchical clustering (with average-linkage and euclidean distance) deterministic?
If I have a dataset called "A" and run n times a hierarchical clustering with average-linkage and euclidean distance on dataset A, will I get n equal clustering solutions (one for each run)?
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Is the copula function invariant only under deterministic monotonic transformation?
I read about the following theorem (see Proposition 3 in the picture below) on the invariance of copula under monotonic transformation, my questions is:
1. Are the $T_i$ mentioned in the following ...
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12 views
What value does the deterministic policy take in an DPG objective function?
I have a doubt with the following paragraph, my doubts are quite basic:
In the last 2 lines about deterministic policy, since it is deterministic, that is a single action would be taken given a state,...
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26 views
How to “convert” deterministic model to stochastic?
Hello dear forum members,
I am seeking your feedback on the question that I have limited knowledge about (i.e., stochastic modeling).
Say, I am working with a variant of a standard epidemiological ...
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0answers
15 views
Is Determinism important for Hyperparameter Tuning?
When training the Model on GPU, different results are retrieved for the same hyperparameters. This effect can be shut down by using CPU or Tensorflow 2.1. with deterministic settings.
The Post on ...
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26 views
How to find the factor which is more contributing to an event
I have two datasets.
Dataset#1 consists of information of patients having one of the three diseases and the hospital they are treated. Each patient will have only one disease.
...
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1answer
82 views
Differences between realization of the random variable and deterministic variable?
The first question is that can we classify variable into random variable and deterministic variable?
The second question is that The possible values taken by a random variable"X"(Uppercase) are termed ...
2
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1answer
234 views
Generate value of variables for given correlation coefficient
I would like to generate test data for script used for correlation analysis between quite long variables.
Is it possible for a given length of vectors, to generate in relatively simple way ...
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49 views
Deterministic Assignment to Treatment
When estimating causal effects, you want to compare individuals as similar as possible. It is from this need that stems the exchangeability (/ignorability) or conditional exchangeability (/ ...
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2answers
133 views
How can we best explain causality for the uninitiated?
How can we best explain causality in layman's terms?
There seem to be two main types of causality. One is probabilistic causation, the other is called determinism in philosophic circles or just ...
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1answer
254 views
Are Gaussian Mixture Models stochastic or deterministic?
Each time we generate a gmm model, we obtain slightly different clusters. Can we hence say gmm is stochastic? We obtain the same clusters if a random seed is set; does this mean given a random seed, ...
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2answers
580 views
What is the difference between Markov chain approximation and variational approximation?
I know they are two different approximation approaches to explicit models(which require approximation, that is transforming a non-optimization problem to an optimization problem to avoid the ...
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1answer
1k views
What are some examples of application of reinforcement learning to systems without stochastic dynamics?
We typically see examples of reinforcement learning problems modeled as a Markov Decision Processes wherein the state transition probabilities are specified. If the system of interest does not have ...
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14 views
Evaluate the probability of my experiment being deteministic AKA what tis the chance of something which has never happened happening? [duplicate]
Short version
Imagine I run the exact same experiment $n$ independent times and get $n$ times the same result. Can you put a lower bound on the probability of getting the same result the $n+1$ time I ...
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0answers
587 views
Stochastic or Deterministic Trend: Supported by the Augmented Dickey-Fuller Test
Below are the sequential steps/question regarding my problem:
I am attempting to specify a VAR model in order to analyze impulse response functions. In plotting my first variable (Figure 1) I ...
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1answer
155 views
Monte carlo simulation to forecast growth of a loan portfolio
I have to forecast the future gold loan portfolio growth of a financial firm. I have past 36 month growth data.
I am planning to use Monte Carlo simulation to forecast, but growth is a deterministic ...
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2answers
242 views
Deterministic classifier and input features
I call the function estimation based classifiers as deterministic, the ones which estimates the $f(x) = a'x+b$ directly, rather than estimating the conditional or joint probabilities directly. For ...
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216 views
How to describe deterministic optimisation algorithms using statistics?
I am solving a large set of nonlinear optimisation problems using different algorithms. I have compared their performance using performance profiles (see Dolan and Moré, 2002). These profiles are ...
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3answers
13k views
What is the difference between deterministic and stochastic model?
Simple Linear Model:
$x=\alpha t + \epsilon_t$ where $\epsilon_t$ ~iid $N(0,\sigma^2)$
with $E(x) = \alpha t$ and $Var(x)=\sigma^2$
AR(1):
$X_t =\alpha X_{t-1} + \epsilon_t$ where $\epsilon_t$ ~...
3
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0answers
633 views
Specifying deterministic terms in VECM in case of logarithmic varriables
I have constructed a VEC model to study real housing price dynamics in relation to demographic demand, real GDP and costs of mortgages. However, I am stuck with the choice of deterministic terms.
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1answer
35k views
Explain what is meant by a deterministic and stochastic trend in relation to the following time series process? [closed]
Explain what is meant by a deterministic and stochastic trend in relation to the following time series process?
$y_t = c + y_{t-1} + \varepsilon_t$ where $\varepsilon_t\sim iid(0, \sigma^2)$
this ...
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2answers
3k views
Can a random variable be a deterministic function of other random variables yet be independent of them?
I was confused by what it means when a Random variable is a deterministic function of another Random variable yet is independent of it? How is this possible?
Here's the question: Consider three ...
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1answer
157 views
Simulator - a deterministic function of random variables
In this paper, the first discussion (Universal latent variable representation by C. Andrieu, A. Doucet and A. Lee) authors state that
Sampling exactly $Y \sim f(y|\theta)$ on a computer most often ...
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2answers
5k views
Are linear classifiers (SVM, Logistic Regression) deterministic?
I am just starting to learn about classification and have been playing around with some linear classifiers. I was wondering if linear classifiers are deterministic--given the same model parameters and ...
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27 views
Existence of data when mean vector and covariance matrix (p.s.d.) is fixed? [duplicate]
I would like to prove that for any positive semidefinite matrix $\Sigma_{n\times n}$ and any vector $\mu_{n\times1}$, are there always data points (no matter how many, as long as finite) whose ...
5
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1answer
1k views
Deterministic sampling from discrete distribution
I'm working on a generalization of the Min-Hash algorithm to allow the meaningful comparison of ordered values such as integers. The core trick is to use deterministic randomness as a replacement for ...
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2answers
4k views
Variance and covariance in the context of deterministic variables
Questions:
Can we talk about:
variance of a deterministic variable?;
covariance between a deterministic variable and a stochastic variable?;
covariance between two deterministic variables?
Are these ...
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0answers
4k views
What is the difference between a stochastic and a deterministic trend?
Models with stochastic trends i.e., structural time series models are useful in some instances. Firstly, it may be hard to identify multiple structural breaks in the deterministic trend when the ...
