Questions tagged [synthetic-data]
The synthetic-data tag has no usage guidance.
0
votes
1answer
24 views
Generation of synthetic data for Hierarchical clustering
I wanted to test various hierarchical clustering algorithms to check which algorithm performs best. For this, I was considering simulating some ground truth. Is the possible to generate a correlation ...
0
votes
0answers
4 views
How wrong is it to simply average Anderson-Darling results for multiple dimensions?
I have $N$ sets of synthetic data and a single set of observed data. I need to know which of those $N$ synthetic sets has the largest probability of having arisen from the same originating ...
0
votes
0answers
8 views
Combining treatment units for synthetic control method
Cross-posting this from the Stata forum to increase visibility - but let me know if that's an issue!
I am thinking about using the synthetic control method to evaluate an intervention that took place ...
0
votes
0answers
19 views
Using Synthetic Data Based on Real Data for Classification
The goal is to classify three different cell types based on certain features (e.g. area, shape tensor etc.). However the amount of labelled training data I have is very small.
Therefore, it was ...
0
votes
1answer
10 views
Synthetic Control Method with Correlated Variables
I am interested in using the Synthetic Control Method to measure the effects of a certain policy. I am afraid that the synthetic control will not be accurate because the underlying variables that make ...
0
votes
0answers
18 views
Manipulating samples with Extreme Value Theory
First of all, i'm an electrical engineer and i know very little about statistics and probability. In one of my work, i'm trying to somehow combine(this word might be wrong..) Extreme Value Theory and ...
1
vote
0answers
32 views
Creating synthetic data from existing data
I have data with 8 features and 900 rows each. Those features are dependent on each other in some way. I want to conduct machine learning, but the data size is small.
I was suggested to generate ...
2
votes
0answers
44 views
Generating Correlated Random Variables following Weibull Distribution
I am working on analyzing power generation from geographically distributed wind farms. I have wind speed data that have been collected at multiple locations, but the measurement periods for different ...
0
votes
0answers
38 views
Bayesian inference on multiple datasets
I have a data-set of synthetic observations that contain an x, y and z component.
The model parameters used to make it is known, including the noise level added.
I am using a probabilistic ...
0
votes
1answer
18 views
Sample whole number from distribution with average less than 1
I am trying to create some simulated data, where for each participant, the average number of events that occur in a given week can be any positive number, but usually in the range of 0 to 5. Trouble ...
0
votes
0answers
46 views
Handling imbalanced data for classification [duplicate]
What are the best ways to deal with imbalanced datasets for classifying whether or not individuals pay their tuition? The data is 75% positive class (paid) and 25% negative (unpaid). Some approaches I ...
0
votes
0answers
488 views
“Add White Gaussian Noise with SNR” vs. “Add 5% Gaussian Noise”
I have a noise-free dataset which is a vector of numbers, $\mathbf{d}$, with length $N$.
I want to "add noise" to this data. My understanding is that there are two ways to do this.
1) Add some ...
7
votes
1answer
60 views
Creating an Imbalanced Dataset
I would like to have my trained model tested on an imbalanced dataset. Is there any algorithms available to generate synthetic data from a balanced labelled dataset (spam/non-spam)?
0
votes
0answers
58 views
Constructing a synthetic treatment group using Synth
Synth is a package for R that enables one to construct a synthetic control group.
It constructs a synthetic control group based both on predictors, and on the dependent variable.
https://www....
1
vote
0answers
46 views
Methods for generating regression data whose target follows an arbitrary distribution
I'd like to generate a regression dataset (independent vars that combine somehow into a target or dependent variable). Generating such a dataset is, in general, easy: we can e.g. pick some $x_i$ at ...
3
votes
0answers
39 views
Is it possible to use a time series to construct a synthetic control variable?
Imagine I want to reconstruct a counterfactual euro-dollar exchange rate in 2010 using a synthetic control variable to assess the impact of some policy. Could I use, for example, the exchange rates ...
0
votes
0answers
145 views
Generalizing “Causal Impact” synthetic controls, to multiple outcomes
Does anybody know a way to generalize the use of the Causal Impact google R package to multiple outcome time series?
Say I ran a time series experiment and was able to set up multiple test outcome ...
1
vote
1answer
141 views
Generating synthetic data for robust regression?
I was running some test to see the benefits of using robust regression over ols. For that purposes, I created synthetic data in the following manner, A is the ...
0
votes
2answers
69 views
Generating a synthetic dataset from a latent class model
In latent class analysis, the estimated model paramters are class sizes and item-response probablities in each class.
Based on these basic parameters, is it possible to generate a synthetic sample ...
1
vote
0answers
42 views
How to evaluate whether the mean of the synthetic time series is statistically equal to the historical mean
I am testing a stochastic model that generates synthetic hydrologic time series (five-year series, 60(month) data points). I want to evaluate whether these synthetic time series have the same ...
1
vote
0answers
44 views
Using fake datasets to optimize a model
I have a machine learning application I'm working on that will make predictions based on data about retail stores. Problem is, any data collected by BI regarding the performance of a given retail ...
1
vote
1answer
25 views
Generating a matrix so that correlations amongst columns are close to pre-defined values
I want to generate a matrix of values such that the correlations (e.g., Pearsons correlations) are close to a pre-defined set of values (e.g., ...
0
votes
1answer
49 views
Over-fitting because of Artificial Synthesis of Data
In the process of artificial data synthesis in Machine Learning applications, when we introduce noise to generate new data, is it possible that overfitting can occur because we are essentially ...
3
votes
0answers
66 views
Is it possible to determine if a dataset is real or randomly generated?
I've been tasked with developing regression and classification models for time series data. For each observation I have a continuous target for regression and a discrete target for classification.
I'...
0
votes
0answers
105 views
When to use synthetic data and when to use regularization parameters to avoid the over fitting and which is better?
Can anyone explain me when to consider generating the synthetic data or when to consider regularization parameters to reduce the error so the machine learning model will not overfit
0
votes
1answer
34 views
Synthetic Control when leaving treatment
I'm trying to do a comparative analysis using synthetic control to compare a country that went from a dictatorship to democracy to it's dictatorial synthetic twin.
As I understand it, synthetic ...
0
votes
0answers
23 views
Validating decomposition of Synthetic Tensor generated from Unevenly Sampled Tensor
I have a 3-way tensor generated from 7 experiments, with each experiment being matricized and becoming a frontal slice of the tensor (thus mode-3 is of length 7). The data is generated from ...
1
vote
1answer
58 views
How to build Predictive models with insufficient historical/performance data
I'm building a auto loan probability of default model where the loan term could be 3 to 7 years and hence default can happen anytime in that interval. But we are a start-up and have only 3 years of ...
3
votes
1answer
575 views
Create synthetic data with a given intraclass correlation coefficient (ICC)?
I want to generate some synthetic data with $I$ observations across $J$ clusters. Additionally, I want the intraclass correlation coefficient ($ICC$) to be an input of my data generation process. So, ...
0
votes
2answers
232 views
Generate non-random data that follows a given correlation matrix
Problem: I have to generate in R a synthetic dataset which contains three different variables that didn't follow any known distribution.
What I did until now: Grouping historical values of each ...
3
votes
0answers
330 views
How to generate synthetic data with a given $R_{x,y}^2$
I would like to generate some data with the following relationships:
$ y = x\beta + T\delta + \varepsilon $
$ R_{x,y}^2 = a $, where $a$ is a number that I can choose when generating the data
$ \...
0
votes
1answer
322 views
How to evaluate the quality of a synthetic dataset?
I'm still playing with the data related to the year 2008 of the "Household power consumption" dataset (free to download at UCI Machine Learning Repository). I was able to generate some synthetic data ...
3
votes
1answer
349 views
Synthetic data behaviour different from real data
I'm studying in R a way to generate synthetic data starting from real world data and, in particular, I'm focusing on the year 2008 of the "Household power consumption" dataset (free to download at UCI ...
2
votes
1answer
2k views
SMOTE using unbalanced package in R fails on simple simulated data
SMOTE is a popular method to generate synthetic examples of the minority class in an unbalanced-class data set.
I am trying out SMOTE in the "unbalanced" package in R. I am generating a simple ...
0
votes
1answer
219 views
regarding generating synthetic data simulating the real data
We are trying to develop some predictive models. The current scenario is that we have to rely on synthetic data at first since the real data set will not be available quite soon. It is understandable ...
0
votes
0answers
398 views
Monte Carlo Simulations: Can I Use Real Data as Universe?
In Monte Carlo simulations, it is a commonly used procedure to generate synthetic data based on a large survey (e.g. a microcensus) first. These synthetic data is then used as universe/population for ...
0
votes
1answer
228 views
Synthetic datasets for concept drifting data
Is there any synthetic / artificial datasets for concept drifting data? I want to visualize the performance of some clustering algorithm when data experiences concept drift and changes over time.
0
votes
1answer
72 views
How to create synthetic mortality data set?
Mortality data for certain countries is available for at the Human Mortality Database (www.mortality.org). However, I would like to develop a multipopulation model that first estimates a mortality ...
1
vote
1answer
2k views
Placebo tests in Synthetic Control Method
I am trying to make graphs for the placebo tests under synthetic control, however I seem to be doing something wrong as I am not being able to merge the files. I am using the dataset of Abadie(2010) ...
1
vote
0answers
60 views
Relation between bootstrap mean and parameter value estimated via maximum likelihood
I have an observed data set $O$ and a synthetic model $S(\theta)$ which attempts to describe it.
By fixing $\theta$ to different values I can generate $M$ synthetic
realizations of the model:
$$S_k =...
7
votes
2answers
289 views
Approaches for generating synthetic survey data with dependent answers?
I would like to produce synthetic survey data. At the moment I produce independent answers between questions according to an arbitrary discrete distribution as in this question.
I want to generate ...
0
votes
0answers
84 views
Create a continuous variable not related to binary target
I would like to create a continuous variable in such a way that it has least predictive information with respect to binary target variable.
That continuous variable needs to have good relationship ...
5
votes
2answers
758 views
Synthetic Control Method
I came across this journal http://www.hks.harvard.edu/fs/aabadie/ccsp.pdf which basically uses Synthetic Control Method (SCM) to estimate the difference between the impact on a variable when an event ...
0
votes
0answers
51 views
Simulate microarray technical error
I need to simulate some microarray experiment datasets. I have the levels of expression of a set of synthetic genes in different experimental conditions. For simplicity of the method this levels are ...
0
votes
0answers
409 views
Generating artificial experimental data to test model fitting software
I wish to test some model fitting software and I would like to generate synthetic datasets for this test. The synthetic data is supposed to originate from a experiment that measures the change in ...
3
votes
1answer
595 views
Generating non-homogeneous spatial Gaussian data
I want to generate a spatial data following multivariate Gaussian distribution.
However, I don't want it to be homogeneous, meaning I don't want the correlation/covariance to be homogeneous. I want ...
1
vote
0answers
212 views
Generate synthetic data from a graph (e.g., bipartite)
Does anyone know of literature describing methods for generating synthetic data from a graphical structure that has been learned from observations of real data? The graph, depending on the type of ...
1
vote
0answers
534 views
Simulated Microarray data [closed]
I would like to generate synthetic microarray data sets for simulation purposes.
The web and literature search so far returned the following:
Microarray Simulator - It provides Matlab skripts to ...
3
votes
1answer
1k views
Synthetic time series generation
I have a linear model (with seasonal dummy variables) that produces monthly
forecasts. I'm using R together with the 'forecast' package:
...
0
votes
0answers
176 views
Null distribution on synthetic data
I need a sort of review of all (or most of) available methods to create null distributions (as reference) to use to compare a result. For ex: if I want to validate a network I can create a set of 1000 ...
