Time series are data observed over time (either in continuous time or at discrete time periods).

learn more… | top users | synonyms

1
vote
0answers
15 views

ANOVA on unevenly spaced time data

I have a dataset with three treatments (P+, P- and T) and want to test the effect of the treatment on the mortality (continuous variable). Data are unevenly spaced in time. I decided to handel this by ...
0
votes
0answers
25 views

Interaction in Multiple Regression with Lagged Variable

The problem I'm trying to solve is as follows: X is a strong predictor of Y, both measured at time T, controlling for other IVs. Based on theory, some people say this supports the hypothesis that X ...
0
votes
0answers
37 views

Looking for Pattern in Daily Data in Time Series

I have a sample data here for a daily time series and I want to how can I find out if it shows a weekly or 10 day pattern. ...
1
vote
2answers
47 views

Constructing a data set for visualization

I am enrolled in a data analysis course and part of a course, I need to find a time series data set and generate visualizations and predictions based on my understanding of the findings. Instead of ...
0
votes
1answer
38 views

How is Gram-Schmidt procedure used in the following time series context?

I was reading the innovation algorithm in Brickel's Time Series Theory and Methods (page 171-172). Let $H$ denotes a Hilbert space, $P$ denotes the projection operator and $\bar{sp}$ denotes closed ...
0
votes
0answers
16 views

On the prediction mean square error of a model

Suppose my model is $y_t = \alpha + \beta t + \epsilon_t$ the l-step-ahead prediction is given by $\hat{y}_{T+l | T} = a + b(T + l)$ where $a$ and $b$ are the OLS estimators of $\alpha$ and $\beta$. ...
-1
votes
0answers
22 views

Best approach to solve this time series classification problem

Hi I have a large data set that contains many time series signals which are labeled to classes, the time series signals look as in the following picture: The time series contain 2000 time samples, ...
0
votes
0answers
10 views

Seasonal Decomposition of Time Series STL NOT WORKING [migrated]

I have a weekly data ts object. ...
0
votes
0answers
7 views

R seasonal decomposition [migrated]

I simulate a time series with periodic and linear components and try to use the R stl function to analyze it ...
0
votes
0answers
12 views

For time series classification, how can k nearest neighbors outperform other models?

Suppose you have a collections of time series data $Y^1,\ldots,Y^N$, $Y^i = Y^i_1,\ldots,Y^i_T$. Your training data consists of labels for some of these $Y^i$, and you wish to infer labels for the ...
1
vote
0answers
21 views

Estimation of fractional order of integration in ARFIMA model

I wish to model monthly EUR/USD exchange rate by an ARFIMA($p,d,q$) model. My question is, how to determine the $d$ parameter of this model?
0
votes
0answers
14 views

How to represent this data as a time series in R [migrated]

I have data set that looks as follows DATE--------TIME--------CONSUMPTION 1.1.2014----04:30-------------40 1.1.2014----05:30-------------60 1.1.2014----06:30-------------50 the data spans for 1 ...
0
votes
0answers
45 views

Should I aggregate my panel data into a single time series for interrupted time series analysis?

I have a very large dataset containing individuals observed daily on some variable Y. I would like to find out whether some event X that occurred simultaneously to all individuals (a global event) ...
2
votes
1answer
79 views

Interpretation of ARIMA with xreg in R

I've fitted a model with auto arima, with independent variables with the below codes: ...
0
votes
0answers
13 views

timeseries graph for every hour [migrated]

my data frame colum deptime(hhmm) has numeric format but some times are missing. I want to plot a timeseries graph for it ...
1
vote
0answers
45 views

What do you think is the right tooling to separate sub-time series from a single big time series?

I would like to separate a big time series into its components to improve forecasting. To clarify: I would like to find the different components - maybe it is better to say frequencies which ...
0
votes
0answers
45 views

Can I use correlation metrics also for time series?

I was using the cross correlation function in R (ccf) until now to discover correlations and lags between two time series. I was wondering if I can use all other ...
0
votes
0answers
38 views

Testing differences in slope in time series of repeated measures data

I have a dataset wherein we measured a response in each sample at 20 time points for 3 different treatments (A, B, C). The response for each sample can be reasonably fit with a simple linear ...
0
votes
0answers
20 views

Measuring effects with longitudinal data

Problem: I have sales data through time e.g. how much each user spent on each shopping trip. I am interested in certain events (think users switching to Amazon Prime for instance). I know the date ...
0
votes
0answers
8 views

Can the coherency spectrum be used as a substitute for cross-correlation?

I know I could inverse Fourier Transform from the frequency domain to the time domain, but let's say I don't want that. Can I make the same conclusions by using the coherency spectrum just as I would ...
0
votes
1answer
30 views

Closed-form expression for autocovariance of random walk with drift

I am working through slides hosted at Basic Time Series Models, and am not sure how to mathematically derive a closed-form expression of the autocovariance of the "random walk with drift" model. The ...
1
vote
0answers
34 views

Which method to use for load forecasting

I have smart meter data set that has consumption readings collected over a year and a half for every 30 mins. What I am trying to do is short term load forecasting. The data set has just three columns ...
2
votes
0answers
26 views

How best to identify candidate error-prone independent variables

I am working on some blood flow data, obtained through doppler. The resulting dataset is a time series, in which each row consists of the following variables: timestamp vessel cross sectional area ...
1
vote
0answers
28 views

Book reading list for Time Series data analysis [duplicate]

I'm looking for book recommendations for Time series Data Analysis. All my time series data is in the engineering domain, pressure, volume, voltage, images etc. I'm experienced in Matlab and mostly ...
1
vote
2answers
58 views

Interpreting ACF and PACF Plot

My raw data consists of a 60-day time series with a downward trend. The data is weekly so the frequency is set to 7. I calculated the difference of the data which looks like this When I run ACF ...
0
votes
0answers
16 views

Clustering objects with missing values

I have some time-series that I would like to cluster, but they can have missing values. One approach that may be ad hoc is to use an algorithm like K-medoids, and to use similarity measure that will ...
0
votes
0answers
20 views

Fitting a model while adjusting for some variable

I plan to figure out the effect of variable X on variable Y. I have time series data for both X and Y and a simple regression model should do the job. Unfortunately the variable Y is also affected by ...
1
vote
0answers
39 views

Cointegration ratio using R for pair trading [closed]

I am hoping to do pair trading using R. To do that, I have to calculate the cointegration ratio between the two stocks. How can I obtain this cointegration ratio using R? For example, I am going do a ...
2
votes
1answer
32 views

Why $E_t(\epsilon_{t+1}) =0$, where $e_t$ is white noise process?

This should be a rather simple mathematical question. Let $\{\epsilon_t\}$ be a white noise process, that is $E(\epsilon_t)=0$ $E(\epsilon_t^2)=\sigma^2$ $E(\epsilon_t \epsilon_s)=0$ for $t \neq s$ ...
1
vote
1answer
28 views

Time Series Hold Out Data not used to build model

It is my understanding that if one wants to build multiple time series models on a time series that goes from 2000 to today (2015) monthly; and one wanted to use that information to forecast 3 months ...
1
vote
0answers
42 views

Time Series using STS( Basic Structural Model)

I am using Basic Structs to forecast my time series. My forecast is exactly overlapping my data. I am sure no model can predict with 100% accuracy. I know I am missing something, can someone point me ...
0
votes
0answers
19 views

How to use R to get drift rate and volatility rate of stock prices changes?

I am doing a research on the historical annual stock prices changes, where I have about 30 rows of annual stock prices. How can I use R to get the drift and volatility rate?
0
votes
0answers
15 views
0
votes
0answers
37 views

How to prove that Innovations in the Innovation Algorithm are uncorrelated?

I tried to search on the internet but could not find a proof... For the innovation algorithm, I am refering to the one used in the time series analysis to predict unknow value.
2
votes
2answers
101 views

PACF for MA(1) process

I have MA(1) process: $X_t=\epsilon_t+\theta\epsilon_{t-1}$ I want to prove the equation for PACF for $n\geq2$ $\alpha(n)=\phi_{nn} = \frac{\theta^n(-1)^{n+1}}{1+\theta^2+...+\theta^{2n}}$ I found ...
0
votes
0answers
41 views

Timeseries forecasting (Cointegration)

I am trying to forecast commodity price fluctuations in a small dataset. The data I am using is here . Does my data have seasonality and Trend? Can someone explain me how to decide that? If my ...
0
votes
0answers
10 views

What is the appropriate way to compare regressions between two time series

I have two temperature time series, both sampled at the same rate and over the same time period. What would be the correct method to compare the slopes of the linear regressions of these two datasets ...
0
votes
0answers
18 views

Can the chi-squared be used to test monthly means for two time series?

Can chi-squared test be applied to compare two continuous random variables but where instead of counts we split samples into groups and into cells of the table we put means for groups? In our case we ...
8
votes
2answers
426 views

Timeseries analysis procedure and methods using R

I am working on a small project where we are trying to predict the prices of commodities (Oil, Aluminium, Tin, etc.) for the next 6 months. I have 12 such variables to predict and I have data from ...
1
vote
2answers
102 views

STL + Random walk failing

We have four months of data (10 minute interval), this seems have nice pattern (at least for eye ball). We are using STL to decompose the time series and apply "random walk" to project next month ...
2
votes
0answers
60 views

preferential multinomial model (with memory)

I am modeling a system that is like having a container of an infinite number of colored balls. On each day $t$, I pull out a new set of $n_t$ balls and I count the number of balls that are red, green, ...
0
votes
0answers
18 views

Distribution of test statistic in ARCH LM test

To test for ARCH effects in a time series, there is the ARCH LM test. Its test statistic is $\chi^2(n)$-distributed, where $n$ is the number of lags in the test regression. But if you have run ...
1
vote
1answer
22 views

How to obtain cross-correlation function from cross-spectrum?

I have implemented a piece of code based on the Lomb-Scargle approach for determining the cross-spectrum of two time series. My cross spectrum contains complex numbers and I have used the basic fft ...
0
votes
0answers
44 views

Augmented Dickey-Fuller Trend and Intercept

I am trying to determine if I should include an "intercept" or a "trend and intercept" when using the Augmented Dickey-Fuller (ADF) test. I ran a regression with my dependent variable and a time ...
-1
votes
0answers
9 views

Add columns and Arithmetic with Time in R [migrated]

I`m new in R. I have a table in .csv format with 12K rows like below: ...
1
vote
0answers
32 views

Arima modeling with limited data

Our 250 weekly datapoints are shown in the figure, along with correlograms of 1st differences. Are we correct to conclude, from overdifferenced correlogram, that for this process we should have much ...
0
votes
0answers
26 views

Questionable Output from Time Series Forecast Using MSTS and TBATS from R forecast package

Using historical daily order totals, I'm wanting to forecast the totals of the next 7 days. It's known in my field that these totals fall subject to weekly and yearly seasonal trends. Called ...
1
vote
1answer
40 views

Time series periodicity bootstrapping

I'm interested in analysing the periodicity of a parameter X, measured over time on cells. The method I am using is destructive, so I cannot follow the same cell over time, but I am rather measuring ...
0
votes
0answers
10 views

Correlation/similarity binary time series

Which are the best or most used methods to find similarities between binary time series? ...
0
votes
0answers
5 views

How to obtain cross-spectrum using the Lomb-Scargle approach?

I would be interested if you could direct me to an implementation in R for finding the cross-spectrum because all the implementations I have seen deal just with the power spectrum.