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1answer
16 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 ...
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0answers
34 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 ...
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0answers
23 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
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1answer
32 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)?
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0answers
20 views

How to generate synthetic data with specific spatiotemporal correlation

My dataset represents a field evolving over time, so has dimensions [X,Y,T]. I would like to generate synthetic data with the same autocorrelation structure and spatial correlations as the real data (...
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0answers
27 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....
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0answers
34 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
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0answers
37 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 ...
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0answers
16 views

Is it possible to create a synthetic population using iterative proportional fitting independent of geography?

I want to create a synthetic population (e.g. of a country) using IPF methods but I do not have interest in geographical/spatial disaggregation. Is it possible?
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0answers
115 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
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1answer
81 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
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2answers
50 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
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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
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1answer
42 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 ...
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0answers
211 views

How do I best go about generating synthetic data with anomalies?

I have sensor data for which I wish to build an anomaly detector. This data, unfortunately, does not contain any anomalies. Consequently I would like to generate synthetic data that contains anomalies,...
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0answers
88 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
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1answer
26 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 ...
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0answers
22 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
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1answer
54 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
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1answer
415 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
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2answers
170 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
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0answers
284 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
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1answer
214 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
275 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 ...
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0answers
160 views

Generating synthetic GPS trajectories based on a sample of real data

I have some moving object trajectories for vehicles (with vehicle ID numbers labelling each lat/lon co-ordinate), and I would like to generate some more data that is synthetic, but realistic. Ideally, ...
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0answers
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
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1answer
173 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 ...
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0answers
314 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
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1answer
182 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
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1answer
65 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
1k 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) ...
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0answers
50 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
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2answers
250 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
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0answers
82 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 ...
4
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2answers
629 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 ...
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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
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0answers
375 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
567 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 ...
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0answers
204 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 ...
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0answers
511 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
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0answers
174 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 ...
3
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0answers
1k views

Why do I get 100% error rate in unsupervised random forest, and how do unsupervised patterns work in “randomForest” R package

I tried to use random forest to classify microarray data. Basing on research of L.Breiman and Tao Shi, I constructed a synthetic data base using bootstrap methods (Assuming it is a matrix with samples ...
2
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0answers
169 views

Generating likely populations given a subsample and control totals

Context In transportation planning, agent-based microsimulation is a method to deal with the complexity of the problem. Instead of computing aggregate flows (as in the classical four-step model), ...
24
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2answers
14k views

What are some standard practices for creating synthetic data sets?

As context: When working with a very large data set, I am sometimes asked if we can create a synthetic data set where we "know" the relationship between predictors and the response variable, or ...