2
votes
2answers
60 views

Capturing Seasonality in Multiple Regression for daily data

I have a daily sales data for a product which is highly seasonal. I want to capture the seasonality in the regression model. How I can do it? I have read that if you have quarterly or monthly data, in ...
0
votes
1answer
33 views
+50

R: Fitting a model with periodic, nonlinear and categorical components

Can anyone give me some advice on how to fit a model with linear (some categorical), non-linear and time series components in R? I don't want to use a non-parametric model like a Loess smooth or ...
2
votes
1answer
19 views

Can I difference after fitting a time series regression model?

Suppose that I have a time series that exhibits a notable trend, and I want to test a hypothesis that a second variable is related to that trend. I fit a linear regression model with that second ...
1
vote
1answer
22 views

ARIMA modeling with more than one Categorical Variable

I am using auto.arima for forecasting. I have more than one categorical variables having more than one level. My questions are : Do I need to do dummy coding ? ...
1
vote
0answers
58 views

F-statistic value is too high for my model

Number of obs = 501 , Method: Fixed-effects regression Number of groups = 101 F( 10, 100) = 3422.31 , Prob > F = 0.0000 , ...
0
votes
1answer
52 views

How to forecast time-series bounded by [0,1], i.e., forecast relative frequencies?

I am working with time series values which are all in the closed interval [0, 1]; these values represent relative frequencies, i.e., empirical probabilities. I would like to create a model such that ...
0
votes
0answers
34 views

Turning general regression into time-series prediction

Suppose you have a general regression model, which behaves like a black-box to you. All you have is a $\ \ \text{train}(X,Y) \ \ $ function, where you input your predictor matrix $X \in \mathbb ...
1
vote
0answers
14 views

How to fit two or more datasets with different occurence for regression

I want to run a regression in R with different datasets. The question is whether stock performance (daily log return) is influenced by factors like interest rates (the one set by fed or ECB), size of ...
0
votes
0answers
16 views

Regression line fit for linearly increasing data with manual reset

I've a linearly increasing time series dataset of a sensor with value ranges between 50 to 150 on which I've implemented a simple linear regression algorithm to fit a regression line, and I'm ...
1
vote
2answers
183 views

Estimate ARMA coefficients through ACF and PACF inspection

I know that this is probably a question that's been asked plenty of times, but i haven't seen an answer that's both accurate and simple. How do you estimate the appropriate forecast model for a time ...
1
vote
2answers
23 views

Can time be squared to develop a curvilinear model of crop yield against time?

I am developing a linear model of yield against time (33 years of yield data) where year is 1975,1976....2007. I want to know whether change in yield over time was linear or not. So I fitted a linear ...
1
vote
1answer
38 views

How can I detect spurious regressions results?

I run bivariate Granger-causality regressions. Let $y_{t}$ and $x_{t}$ be stationary time series. I test if $x_{t}$ can forecast $y_{t}$ with the following regression: $$y_{t+1} = \alpha + ...
2
votes
1answer
94 views

Can First Differencing Cause Negative Serial Correlation

Ex. series, say stock prices 103 101 102 150 101 102 100 First differenced 2 1 48 -49 1 -2 Notice you could guess a very large negative number following the very large positive in the first ...
0
votes
0answers
48 views

Mixing two linear regression models

In time series analysis, I have one predictor $X_1$ that has a higher $R^2$ when regressed against $Y$ sampled at 10 minutes interval. Another predictor $X_2$ has a lower error when fitted against $Y$ ...
1
vote
0answers
32 views

Estimating a first order plus dead time model

The data generating process is given by the following differential equation: $y(t) = a + b u(t - \theta) + c \frac {dy} {dt}$ Now imagine having as data a long time series for both $y$ and $u$. If ...
2
votes
1answer
59 views

Why could mean centering change results

I used centering for my variables due to multicolleanirity and surprisingly the results (from before to after centering) changed for two interacted variables; one from significantly negative to ...
0
votes
0answers
26 views

Centering vs. Standarizing which one is better? [duplicate]

Two approaches have been proposed in order to overcome the issue of multicollinearity if we have interaction variables which are mean centering and standardizing (z scores). You can check No.2 in this ...
1
vote
1answer
33 views

How accurate is F test in panel data

I heard that the F-test is to advice you whether to use fixed effects or pooled OLS. However, I didn't find any details about it in books. Only in a very few studies. What is the hypothesis of the ...
1
vote
0answers
46 views

Is it ok to transform a logarithm variable to z score

I have a variable that has 57 kurtosis, so I decided to transform it to log. However, I have multicolleanirity problem due to interacting this variable and others with another variable so I am using z ...
1
vote
1answer
25 views

Characterizing trend of time series in R

I have a fairly basic statistics application question. Lets say I have a set of four fold-change values, representing the abundance of a factor as it passes through four consecutive time points: ...
0
votes
0answers
6 views

Repeated measures with multiple time points for the predictor and dependent variable: Does Xt-1 predict Yt better than Yt-1 predict Xt?

I have a question on what type of analysis I should be looking into to analyze some data I have: Suppose you have 2 runners X and Y, and they take turns sprinting 100 meters, with runner X going ...
1
vote
1answer
43 views

structural breaks in time series using matlab

in a plot of my time series there is clearly visible that there is structural break, but I have to find the exact date. I want test this with the chow test. Although I understand how to perform this ...
1
vote
0answers
40 views

Time series, x-y coordinates, regression, R [closed]

I have data in the form of these columns: date, x coordinate, y coordinate, value A, value B, value C, value D, etc. (I don't see the possibility to copy an ...
0
votes
1answer
54 views

Multicollinearity with Interaction (high VIF)

When I check the VIF of my independent variables with the dependent variable, it looks normal and less than 5 but when I add the interaction variables, the VIF increase to 48 for some variables. I ...
2
votes
2answers
61 views

Prove expression for variance AR(1)

For the AR(1) process $x_t = \delta + \phi x_{t-1} + \eta_t$, I am trying to prove that the variance is: $\sigma_x^2 = \sigma_\eta^2/(1-\phi^2)$ And that the first-order covariance is: ...
1
vote
1answer
35 views

Why is an ARMA model a parsimonous approximation of an AR model?

I am reading a book on time series and I came across the following: "In addition to being a parsimonous approximation to a high-order AR(p) model, ARMA models...". Why is an ARMA model a (parsimonous) ...
1
vote
1answer
60 views

Time Series Forecasting vs Linear Regression Extrapolation

I'm working on some problems involving prediction of future values. I need to get an aggregated total at some point in the future. My question is: what is the best way to predict the future values? ...
2
votes
0answers
22 views

Is ARIMA(1,0,0)+xreg for level shift the same as linear regression model with level shift adjustment and lag1 term?

I have a time series with a level shift. Thus, when treating it with an ARIMA model, I use arima(1,0,0)+xreg. The xreg is a ...
0
votes
2answers
38 views

how do you do regression analysis on advertising impact

i have data that includes clicks, spend, signups and date. for 1 week, i turn off advertising spend to see what clicks and signups are. the next week, i turn advertising back on to see what the new ...
1
vote
0answers
19 views

Assessing Cannibalization, intervention of new mobile app on monthly sales

I am a beginner in statistics and looking for suggestions from you all on the approach for one of my study. For my study, there is a company which sells products via its online website (lets call it ...
0
votes
2answers
24 views

Question about Time 1/Time 2 analysis

I was hoping to get some input on the best way to test some data that I have collected (using SPSS). In short, respondents make an evaluation at time 1, then complete a distractor task, and then ...
1
vote
1answer
70 views

Finding significant peaks — evaluation of different methods

I have a small doubt. My real data looks like this Y values are random values of integers from 0 to 2000. X values run like 1,2,3,4,5,.. to 2 million. Now, my task is to identify significant peaks ...
1
vote
1answer
29 views

Individual slopes for many zip codes over time

I have a dataset where I am interested in calculating a slope for each observation / row. I have dependent variable $Y$ that is continuous. Every $Y$ is unique to a zipcode. and my independent / ...
2
votes
1answer
94 views

What is the problem with using R-squared in time series models?

I have read that using R-squared for time series is not appropriate because in a time series context (I know that there are other contexts) R-squared is no longer unique. Why is this? I tried to look ...
0
votes
2answers
26 views

Variable creation in time series regression

I have a coworker who wants to create his own independent variable to add to a time series regression model because he believes that his variable will encapsulate more information. Is this advisable? ...
3
votes
1answer
311 views

Choosing the right forecasting technique

I'm currently attempting to forecast visitor data for stores. My dataset includes daily visitor totals of three years. Note that the dataset isn't complete (stores can be closed for a few days, etc). ...
10
votes
4answers
288 views

A regression model whose response variable is the day of year that an annual event (usually) occurs

In this particular case I'm referring to the day on which a lake freezes. This "ice-on" date only occurs once a year, but sometimes it doesn't occur at all (if the winter is warm). So on one year the ...
0
votes
1answer
58 views

Single time-series difference before and after treatment

I am doing panel data analysis. I have N= 103 firms in T= 5 years (that is around 507 observations with an “unbalance data” fixed effect). The study period is from 2008-2012. The period of the ...
3
votes
2answers
61 views

How can I recognize dramatic changes in a set of observations?

I'm trying to build a monitoring system that will automatically raise a warning when a dramatic change happens to some of the observed parameters. My problem looks like this: We send out e-mails to ...
0
votes
0answers
31 views

Stata: Test over time --> Which method?

I am working on a project regarding the influence of temperature and time variables (weekday, weekend, month, season etc.) on the sales of a local bakery. The research goal is to be able to better ...
2
votes
1answer
48 views

Small sample, many observations. Is the sample large enough?

I am working on a project regarding the influence of temperature and other variables on the sales of 3 branches of one local bakery. The research goal is to be able to better predict bakery sales (in ...
0
votes
0answers
21 views

Suggestions - forecasting models

I have been assigned a task where I need to solve a business case. Let me explain what information I am looking for: I have historical data of several products and I need to forecast the time ...
0
votes
1answer
66 views

Equivalent of auto_arima function of R in Stata

I am building a dynamic regression model in Stata which basically has this form: $$Y = a_1x_1 + a_2x_2 +... + e$$ where the error $e$ is then modeled as ARIMA process. Is there a command to find ...
5
votes
1answer
142 views

Hidden state models vs. stateless models for time series regression

This is a quite generic question: assume I want to build a model to predict the next observation based on the previous $N$ observations ($N$ can be a parameter to optimize experimentally). So we ...
1
vote
2answers
118 views

Evolution of slopes over time

Participants in a study are tested on their ability to recall items depending on the number of times these items are presented by day. We follow their performance over a time period of 4 days. So I ...
2
votes
1answer
201 views

Using non-stationary time series data in OLS regression

I am using 1983-2008 annual data to test if both gini coefficients and gross national saving in China and the US can affect the US current account balance. The data seem to be non-stationary, but I am ...
0
votes
2answers
79 views

Is there any tool that can do Vector ARIMA modeling in time series

Vector ARIMA model is used in multiple time series analysis. I am just wondering if there is any software or tool can be used to build the model. Some tools,like R, can only be used to predict the ...
2
votes
1answer
109 views

Building a time series model using more than independent variables

I am working on a project, and I am totally new to statistics. I have sales data for last two years at week level, along with other variables like temperature, holiday (TRUE/FALSE), where holiday are ...
1
vote
1answer
39 views

Using results of regression on raw observation values to approximate results of regression on relative change between observations (Simple, Linear)

this is my first time on Stack Exchange so if I did something wrong please tell me. I have a time series dataset. There is an observation $(y,x)$ for each continuous time $t$. Let’s say for each day ...
0
votes
1answer
52 views

How to extract long run and short run coefficients from ARDL (UECM) estimates?

I have estimated ARDL(UECM) in eviews but I dont know how to specify or extract the long run an short run estimates/coefficienst? what is the standard procedure to do so?