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35 views

Forecasting time series with lagged variables and machine learning

I want to forecast a time series based on the lagged variables of the model and train it using a machine learning algorithm like Random Forest, SVM, Neronal Network, etc. So I want to forecast A ...
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0answers
9 views

Deciding the lag while testing for timeseries data stationarity

I am currently reading up on time series forecasting using ARIMA in SAS. I just began to go through what has been explained here : ...
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0answers
22 views

Lag Selection in an unbalanced panel in R

How to determine appropriate number of lags in an unbalanced panel? Thanks.
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0answers
33 views

What is the difference between “lag order” and “maximum lags”

The R Vars package has a Vector Auto Regression function called var. The arguments include (among other things) "p" defined as the "Integer for the lag order" and "lag.max," which is defined as ...
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0answers
14 views

CCF time lag in minutes in R

I have data sampled every 5m and I want to estimate the ccf between them, in order to do it I prewhiten the time series x and y and then I apply CCF But lags are not direct related with my sampling ...
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0answers
17 views

Estimate VAR model from data about lags

Does anybody have any idea how i would write the var model based on this table? What coefficients should be included? Any hint will be much appreciated. Thank you!
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1answer
43 views

Finding optimal lag order for an exogenous regressor in a VAR model

I can't use VARselect as it gives lags in a VAR model which considers all the variables to be endogenous. In my case, one of the variables is exogenous and affects dependent variable with a certain ...
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1answer
120 views

Distinguish between short run and long run effects

I read in a paper the following sentence: The fact that there is a difference between short-term and long-term coefficients is a result of our specification which includes lagged endogenous ...
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1answer
54 views

Lag length selection for a VAR model

The model I am working on has 4 time series (X, X1, X2, X3). Lag lengths are 5, 1, 4 and 6, respectively. X1, X2 and X3 are stationary at level and X is stationary at second difference. I am applying ...
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1answer
198 views

Lag selection for Augmented Dickey Fuller test

Apologies in advance, I am a beginner so these questions might be quite simple. I am testing log real exchange rates for unit root stationarity for EU15 countries. I was wondering what is the best way ...
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0answers
34 views

lag number in VAR

I am trying to determine the optimal lag number in 2-equation VAR as follows: 1. choose lag based on information criteria 2. estimate the model using # of lags determined above and test for ...
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0answers
41 views

Using lag of variable as a proxy to remove endogeneity- Can I just replace the variable in OLS, or do I have to use 2SLS?

I am running a regression of capital, labour and level of migration on GDP (augmented Cobb Douglas production function). To counteract the endogeneity between migration and GDP (migrants might move to ...
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0answers
48 views

how to specify range of lag in prewhiten CCF using package TSA in R

I am doing time series regression using package TSA in R. I have 2 time series, say x and y, so I started by doing prewhitened CCF. So, 2 issues I have encountered and would really appreciate if any ...
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1answer
133 views

How many lags should I include in the VAR-model

When building a VAR-model with six variables I had the following situation: after building a VAR(1) the overall portmanteau test says that the residuals are ok (p=0.85, p_adjusted=0.22). But when I ...
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2answers
57 views

Conditional entropy and Spearman's correlation based lag in time series

I have two time series A, B. Both are seasonal and B primarily is A driven( other temporal causes may exist). B-Red, A- Green I want to calculate lag of red series with respect to green as clearly, ...
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0answers
66 views

Time domain regression - determining lagged predictors

Determining lifestyle factors affecting a medical symptom I have a dataset with n=200 records corresponding to contiguous days and consisting of 1 continuous output variable (a medical symptom) and ...
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0answers
48 views

Logit: using lagged dependent variable

Is it methodologically feasible to include lagged dependent variable in the logit model?
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0answers
222 views

How to use lagged dependent variables (panel data) in practice?

Working with a panel data set with a daily time series structure I was told to include a lagged dependent variable. The dependent variable is daily electricity consumption of a medium size sample ...
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0answers
108 views

AIC/BIC values keeps falling as I add more and more lags. How do I select the appropriate lag length?

I am trying to minimize the values of the Akaike and Bayesian Information Criteria to figure out the optimal lag structure for my ARDL error correction model. I am using Stata to run my analysis and ...
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0answers
131 views

lag length selection in Vector Error Correction Models

I am doing a VECM analysis in R using vars R package. My problem is to find the lag length of the VECM model to be specified. I a previous post I was suggested to use the VARSelect function. However I ...
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2answers
94 views

R² of 1 with dynlm procedure?

Dear statisticians/programmers, I want to model the price of AXE deoderands in Albert Heijn (a dutch supermarket) as a linear function of its own past (up to two lags) and the past of the price of ...
3
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1answer
89 views

Goodness of fit for a spatial panel with fixed effects and both spatial lag and spatial error

On a dataset, I performed spatial panel regressions with fixed effects, and with both a spatial lag and a spatial error (both are significant), using package splm in R (Millo and Piras 2012 Journal of ...
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0answers
132 views

How do I choose the optimal number of lags?

I am making a model (multiple regression) that predicts credit growth. Many of the independent variables are leading indicators and should therefore be lagged. How do I choose the optimal number of ...
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0answers
77 views

Maximum Lag Length in Granger Causality Test for intraday ,1 minute, time series?

I have 2 time series having 1950 observations each. The time series represent intraday, 1 minute, close prices of stocks. Those 1950 observations cover period of 5 trading days, meaning that each ...
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0answers
47 views

What type of model should I use? (Time series, univariate, dependent variable is a count)

I have a univariate model in which I am looking to predict the number of articles per week in a newspaper about a protest (count data) by how many arrests of protesters occurred per week. I have 148 ...
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1answer
237 views

Regressing a differenced variable on a lagged variable. How can I fix the error in R?

I have a time series (std) of 324 observations with no missing values, starting from January 1987 and ending in December 2013. I want to regress via OLS the one in the question. In R, the code: ...
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2answers
266 views

Residual autocorrelation versus lagged dependent variable

When modeling time series one has the possibility to (1) model the correlational structure of the error terms as e.g. an AR(1) process (2) include the lagged dependent variable as an explanatory ...
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1answer
132 views

Specifying lag in `dlnm` when passing arguments to `crossbasis`

I am using the dlnm package to build a finite distribute lag linear model. I intend on testing the model-fit based on various lag levels to assess which lag is ...
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4answers
1k views

How to perform proper data mining on time-series data?

I have some daily data from city A, B, C. Values from city A are highly correlated with values from other cities for lag -1,-2,-3 and -4. I want to use Random Forest, SVM and ANN to predict values ...
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0answers
239 views

consequences of lagged dependent variables in panel data and how to deal with it?

I have some elementary problems understanding the consequences of using/adding a lagged dependent variable in my predictive model. I’m trying to predict values $Y_{i,t+\tau}$ for $\tau=1-3$ with: ...
3
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1answer
110 views

Backshift operator property not clear

In my introductory book on time series analysis the backshift operator $\mathbf{B}$ is introduced using the following definition: $$ \mathbf{B}x_t=x_{t-1} $$ Then the author sets off to derive some ...
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0answers
148 views

How to estimate a dynamic Tobit model

I have data which correspond to a corner solution. The Tobit-model seems to be adequate for this data. However, I also wants to control for a baseline variable (t-1) and unobserved heterogenity. This ...
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2answers
1k views

What is lag length?

I've been looking up all across the internet to see what "lag length" is. I want to perform an Engle Granger - Augmented Dickey Fuller test, but for ADF, it always asks to specifiy a lag. It seems ...
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1answer
1k views

Multivariant time series in R. How to find lagged correlation and build model for forecasting

I'm new in the page and pretty new in statistics and R. I'm working on a project for college with the objective of finding the correlation between rain and water flow level in rivers. Once the ...
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1answer
175 views

Correlating two time series to account for lag and lingering effects

I am trying to find the correlation between two time series, call them A and B. Let's pretend A has the number of successful advertising campaigns for each month for a company, and B has the company's ...
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1answer
108 views

Autocorrelation for regression

I am attempting to use a significant autocorrelation (where it lies outside a 95% interval around 0) indicating periodicity of a signal and use it as predictive variable in a regression. If, for ...
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1answer
1k views

How is the proper number of lags for ACF or PACF displaying?

How many lags should be used for ACF or PACF displaying if we have $S$ seasonality? For example, for 500 observations I have 25 lags for 200 observations I have 22 lags It is independent from ...
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0answers
139 views

Using kknn regression function with NAs

I have been lurking here for awhile and now have a question I hope to get answered! I am wondering how to get nearest neighbor algorithms to deal with NAs most effectively. I am dealing with a data ...
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0answers
598 views

How to interpret results after including lags in panel data regression (fixed effects)?

I would like to ask a question about lags I've included however I believe it's better if I first give you some more insight information about my topic. My hypothesis is ''the positive sentiment ...
3
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1answer
2k views

Intuition behind cross-correlation function interpretation vs. correlation of lagged time series

Can someone please explain the difference behind WHY the cross correlation function ccf() chooses to keep the same denominator for all lags and chooses to ignore ...
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1answer
563 views

Interpreting Linear Model Coefficients with Lagged Variables

Let's say I have a data set which looks like below and I'm running a linear model to predict income on two predictors. ...
11
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1answer
2k views

When is it necessary to include the lag of the dependent variable in a regression model and which lag?

The data we want to use as dependent variable looks like this (it is count data). We fear that since it has a cyclic component and trend structure the regression turns out to be biased somehow. We ...
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0answers
162 views

Shrinkage Estimator for Newey-West Covariance Matrix

This is a cross post. I would like to apply the Newey-West covariance estimator for portfolio optmization. Up to lag one it is given by $$ \Sigma = \Sigma(0) + \frac12 \left (\Sigma(1) + \Sigma(1)^T ...
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0answers
192 views

Lagged term in time series with stationary errors: too good to be true?

I often have datasets where there are many animals, in several treatment groups, and each animal's body weight is measured at regular intervals over the course of its lifetime. The response of body ...
4
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1answer
339 views

How to fit a model with lagged variables

I am trying to fit a model with lagged variables. The problem is: In a big classroom with windows open, the outside temperature, humidity and solar activity will lead to variation in the ...
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0answers
85 views

Inducing autocorrelation by fitting the wrong ARMA?

I am trying to fit an ARMA(p,q) model to the mean equation of my return series. The problem is, that the acf and pacf are pretty not usable, i.e. it is hard to find a good model to take account of the ...
2
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1answer
214 views

Running a Probit on Survival-Time Data?

Can I run a probit on survival time data? It's discrete-round, and I want to look at whether lagged variables affect the failure event. I am, however, getting negative coefficients for a probit ...
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0answers
89 views

Polynomial distributed lag glms

I am about to use this input for my data but i cant find under which packages does it work. I searched almost everywhere. m<-pdlglm(yy~pdl(zz,4,2)+sin(zz)+pdl(xx,4,4))
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0answers
828 views

How to use Almon model (polynomial distributed lag) in R program

I am testing the influence of intramural R&D expenditure, life expectancy, HDP and tax on the GINI index, but I have a problem because I am trying to make my model better by using the Almon model ...
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3answers
13k views

Inclusion of lagged dependent variable in regression

I'm very confused about if it's legitimate to include a lagged dependent variable into a regression model. Basically I think if this model focuses on the relationship between the change in Y and other ...