The tag has no wiki summary.

learn more… | top users | synonyms

1
vote
0answers
17 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 ...
1
vote
1answer
45 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: ...
1
vote
1answer
32 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 ...
0
votes
1answer
47 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 ...
1
vote
4answers
349 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 ...
2
votes
0answers
122 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
votes
1answer
59 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 ...
1
vote
0answers
38 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 ...
1
vote
2answers
79 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 ...
0
votes
0answers
19 views

Predicting one time series from another if they are related - algorithm in R

I am new to time series analysis; I am not even sure if this is even a TS problem. I have looked at other TS posts, but I have a hard time to translate the responses to my needs. For now I am hoping ...
7
votes
0answers
225 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 ...
1
vote
1answer
74 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 ...
0
votes
0answers
97 views

ARDL, Lag Terms and Singularity

I am interested in fitting an ARDL model that has 4 lags for each explanatory variable. However, when I fitting the model in R. R says that coefficients are not defined because of singularities. Is ...
1
vote
1answer
87 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 ...
1
vote
1answer
275 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 ...
0
votes
0answers
68 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 ...
1
vote
0answers
153 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 ...
0
votes
0answers
82 views

Sum of lagged coefficients (VAR)

I have come upon a paper where a VAR analysis is performed. Using 3 endogenous variables and some exogenous (control) variables, the results of the VAR analysis are shown in a table. For the ...
0
votes
0answers
48 views

What is the problem with my lagged variables?

There are variables a,b,c, and d. Variables a and b is from firm's financial statements and they have time-lag.(financial statements take time to be announced) Variable d is a dummy variable ...
2
votes
1answer
925 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 ...
0
votes
1answer
250 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
votes
1answer
640 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 ...
1
vote
0answers
124 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 ...
1
vote
0answers
122 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
votes
1answer
238 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 ...
5
votes
0answers
73 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 ...
0
votes
0answers
223 views

STATA - Procedure for properly estimating an AR(p)

I'm trying to estimate an autoregressive process AR(p). Following the literature: 1) I checked if the series is stationary or not running the augmented Dickey-Fuller test (as I expected, the ...
1
vote
1answer
112 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 ...
0
votes
0answers
61 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))
0
votes
0answers
552 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 ...
7
votes
3answers
6k 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 ...
1
vote
1answer
236 views

Issues when using interaction term with a lagged variable in R

Today I tried to estimate models using both plm and pgmm functions in the plm R package, with an interaction between ...
4
votes
0answers
559 views

Lag length selection Granger causality test

Consider G-Causality on two stationary time series vectors (call these variables $X$ and $Y$), each with 100+ observations. It's daily financial market time series data. I have reason to believe that ...
1
vote
1answer
316 views

Vector autoregression - number of lags

I am constructing a Vector autoregression model and I have used AIC to find how many lags I should use. Does 7 lags seem unreasonable? I am trying to find the impact the property market has had on the ...
4
votes
3answers
2k views

Creating auto-correlated random values in R

We are trying to create auto-correlated random values which will be used as timeseries. We have no existing data we refer to and just want to create the vector from scratch. On the one hand we need ...
4
votes
2answers
2k views

Correlating volume timeseries

Consider the following graph: The red line (left axis) describes the trading volume of a certain stock. The blue line (right axis) describes the twitter message volume for that stock. For instance, ...
1
vote
4answers
1k views

Lagging over a grouped time series

I have a few tens of thousands of observations that are in a time series but grouped by locations. For example: ...
3
votes
0answers
272 views

Lag Selection Modelling 'Pseudo' Panel Data

I have what I would call a pseudo panel, where my dependent variable varies over time and space (regional death counts), but my x variable of interest does not (national wage time series). Basically, ...
4
votes
2answers
637 views

How to account for lag in a simple regression in R?

I'm trying to do a regression with data over time, and where I suspect there may be a lag component in the relationship between my dependent and independent variables. I've actually found some data ...
2
votes
0answers
226 views

Using autocorrelation plots to choose the number of inputs for a neural network predicting time series

A neural network applied to time series needs to have the number of input nodes defined. Each input is applied to a time point previous to the current point being predicted. If $D$ is the number of ...
1
vote
2answers
609 views

What is wrong with lagged regressor in time series regression?

I am trying to explain a time series with the help of other related series. I really get nice fits using a standard LM approach with NeweyWest VC matrix. The fit even increases drastically when I ...