Time series are data observed over time (either in continuous time or at discrete time periods).
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17 views
R plot time series data: Extremely Short time laps [migrated]
I have the following data frame. The gaps between time slots are different, sometimes small, sometimes large:
...
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0answers
32 views
Cross correlation for extremely highly correlated series
I have two time series showing very high dependency, in the order of 99.99% correlation, and I need to study their lead-lag relationship. So far I've been looking at the Pearson correlation with 7/8 ...
2
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2answers
180 views
How to calculate multi-step prediction intervals for time series data?
I need to manually calculate multi-step prediction intervals for time series data. I know packages like 'forecast' in R provide these, but I cannot use these packages as the production infrastructure ...
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1answer
43 views
Program Impulse Response Functions for VAR
I'm trying to program impulse response functions for a VAR model using Cholesky decomposition. The thing is I do not completely understand how I should do this when I read in the literature. Suppose I ...
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1answer
39 views
How to estimate certain parameters of an AR model in R?
I need to estimate parameters of an AR model which is in the form of AR(1,11) it means that coefficients of AR orders from order 2 until order 10 are zero. How can I estimate these two parameters in ...
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1answer
64 views
What to do about Seasonality Patterns in ACF, Time Series Data
I'm dealing with a time series data and I'm trying to construct a time series model for this particular dataset. I'm new to R and tried using the the auto.arima ...
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1answer
57 views
Degrees of freedom for Gaussian Process
I am reading this paper on Generalised Wishart Process (GWP). It is about modelling covariance matrix of D - dimensional gaussian processes (GP) as GWP. I fail to understand interpretation of "degrees ...
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0answers
48 views
Forecasting of highly correlated time series
In time series forecasting using various models like AR,MA,ARMA, etc, we usually focus on the modeling of the data in the change of time. But when we have 2 time series that Pearson correlation ...
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20 views
dickey-fuller and regressions
I have searched the internet on this, but I could not find any book/lecture/... that relates the ADF test and OLS regressions in practice.
Here are my questions:
1) it seems to me unclear what model ...
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29 views
Autocorrelation impact on the Coefficient of Variation
Many articles use the Coefficient of Variation (CV) to report variation in time series.
But isn't the standard deviation, used to measure the CV, no more reliable when autocorrelation is present ?
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1answer
53 views
Tests to establish correlation
I'm trying to analyze if there exists any correlation between two time series? So far I have not been able to notice any significant correlation.
So if I were to assert in my report that these time ...
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0answers
48 views
How do I test for significant difference between sets of time ordered data?
I have data about activity on a game site over a period of time (~1.5 years). I want to compare a sub-population's activity between certain time segments so that I can say things like "Group A played ...
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0answers
21 views
Deciding if my mutant strains are significantly different from my wild type from data measured over time or from gradients
I have a set of data which is the oxygen consumption of a wild type (WT) and a few mutants. I averaged the data and plotted graphs with each mutant and WT series and plotted a line of best fit. Is ...
1
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1answer
59 views
Calculating the corr. coefficient between returns of portfolios in EXCEL
I want to determine the correlation between the returns of a portfolio with returns of the market (suitable index). To find how the portfolio performs in bear resp. bull markets, I want to calculate ...
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0answers
41 views
Efficient numerical methods to estimate ARMA models?
I mean exact likelihood based estimation instead of these LS methods.
There are more general nonlinear optimzation methods, but in terms of performance, are there any specific methods for this type ...
5
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2answers
112 views
spatial autocorrelation for time series data
I have a 20-yr dataset of an annual count of species abundance for a set of polygons (~200 irregularly shaped, continuous polygons). I have been using regression analysis to infer trends (change in ...
1
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1answer
135 views
Help interpreting ACF- and PACF-plots
My ACF- and PACF plots are illustrated below:
The first one is in original scale and the second picture is zoomed. What process would you classify this? AR, MA or ARMA? =)
Thank you for any ...
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46 views
“system is exactly singular” in R function BoxCox.ar
I'm trying to perform a Box-Cox transformation on some financial data (SPY).
The BoxCox.ar function (in the package TSA) gives me the following error:
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1answer
66 views
Kernel PCA (in R)
I am attempting to use the kernel PCA features in kernlab but am having trouble understanding the output. In particular, it's unclear what scale the results are in ...
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1answer
90 views
Positive & negative shocks in a VAR model and impulse response function in R
I have two general questions about impulse response functions in R using the package vars. Take a look at this code:
...
3
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2answers
62 views
Smoothing algorithm for irregular time interval
I have various sets of irregular interval time series data to which I want to apply some sort of smoothing algorithm to produce a good fit.
I have attempted various methods which all were ...
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0answers
21 views
Multiple comparisons of multiple groups over multiple years
I have 14 years worth of data. For each year there are 5 possible payers for the trauma care delivered. I want to compare the significant changes of payers over time. Specifically that one of them ...
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1answer
46 views
Non-causal of variable threshold algorithm
I'm not entirely sure this question belongs here. (Maybe better suited on stackoverflow or theoretical computer science). But here it goes.
I'm reading a paper called. "Time-Frequency Analysis of ...
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1answer
50 views
Can I use xreg with stl decomposition to handle moving holiday?
I am trying to decompose and forecast a weekly time series which is believed to be affected by moving holidays (e.g. Chinese New Year, which happens in different weeks of a year).
I would like create ...
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1answer
42 views
Compare increase rate over time 2 groups
If you have two groups lets say Y any Z that change over "time", how do you compare if the increase rate of x and y over time is same or not. How would i set this up in R
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1answer
71 views
how to test heteroskedasticity of a time series in R?
How can I test heteroskedasticity of a time series in R? I have heard of two tests McLeod.Li.test and bptest (Breusch-Pagan ...
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60 views
How to calculate confidence interval for autocorrelation- and cross correlation functions?
I would like to calculate the confidence interval for my autocorrelation function. Does this calculation differ in any way from the normal way of calculating confidence intervals? How would I ...
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0answers
33 views
Patterns in binary sequences
I have data that looks like this:
011100111110100111
111111111111110010
111100001111000011
1D lanes of streams of data. Each row signifies the presence of a ...
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4answers
88 views
How to prove statistical significance between the 4 seasons
I have data regarding the number of deaths in a city over 35 years. I've collated the data, and now wish to prove the difference in total number of deaths between seasons is significant. Spring has ...
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0answers
39 views
How to decide the order of my ARMAX-model for each component?
I'm doing time series analysis with 78888 x 8 matrix of data.
The matrix includes the response data (the series I'm interested in predicting) and exogenous data. The data is hourly sampled and ...
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4answers
111 views
How do I get better forecasts for this data
How do I get better forecasts for my model? Is the plot supposed to look like this? I am using the code:
fit <- auto.arima(blah)
fcast <- forecast(fit,100)
...
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1answer
89 views
Constructing a VECM with a mix of I(0) and I(1) variables
I've been using the Johansen Procedure to check and correct for cointegration in my model, by estimating a VECM instead of VAR. But now I want to estimate a new model, in which I expect the same ...
-1
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1answer
72 views
How to get p-values for model
I am using the example from Shumway's book. How do I get the p-values for all the coefficients? Do I divide the coeffients by the standard errors?
...
3
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0answers
34 views
How to form a confidence band around the trend fitted from time series data
I have a time series data set. I can decompose it and get the trend but I would like to put confidence ranges around the trend (past) not the forecast-ed component. The decompose function also ...
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1answer
57 views
Time series forecasting
I create time series model via:
model = sarima(data,1,0,1)
sarima.for(data,100,1,0,1)
The model diagnostics look good and indicate that the model is a good fit. ...
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1answer
52 views
Ljung-Box Statistic
Suppose I fit an AR(2) model to a dataset and get the diagnostics. If the Ljung-Box Statistic is significant for all lags for a time series model what is the interpretation of that? Does that mean ...
2
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1answer
99 views
ARIMA forecast with seasonality and trend, strange result
as I am stepping into forecasting with ARIMA models, I am trying to understand how I can improve a forecast based on ARIMA fit with seasonality and drift.
My data is the following time series ( over ...
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1answer
47 views
Adding exogeneous variables to a GARCH model
I am somewhat new to R and am currently stuck with the following problem:
I have two Variables X and Y . In the first step I do a GARCH(1,1)
fit on Y. In the second stepd I would like to input X as ...
2
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1answer
77 views
Analysis of discrete (count) time-series data
I have a 2X2 factorial experiment where I am interested in seeing the effect of two different nutrient solutions (N and W) on the appearance of root tips of two different plant species (A and B). I ...
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0answers
71 views
How to identify a congestion in a time series?
Here some examples of what I mean by "congestion". What would be the best way to identify this in a timeseries in R?
Rules are:
Two separate maximum (upper side)
Two separate minumun (lower side)
...
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1answer
56 views
Question about sample autocovariance function
I am posting this question here, because I didn't get an answer from math-exchange... =)
I'm reading a time series analysis book and the formula for sample autocovariance is defined in the book as:
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1answer
65 views
Modelling two correlated variables
I wish to simultaneously predict two correlated time series. Here is a plot of one time series against the other:
At the moment I have separate linear regressions for both of them which rely on ...
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1answer
48 views
One step ahead forecast with SEASONAL data collected sequentially
In this post it was asked how to do one step ahead forecasts using Arima form the forecast package. Now I'm using an example with hourly seasonal data and would like to do something similar but the ...
1
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1answer
46 views
Automatically detect “bimodal” curves in a large number of short time series
So, I have a huge number of amplitude modulated waves and I am attempting to determine which modulation parameter modulates each time series. To do this, I folded each time series over at the ...
7
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2answers
111 views
What are some good resources for the history of time series analysis?
I have checked out the answer to this question on stats.stackexchange: What are good resources providing a history of statistics? Indeed, the Stigler book "Statistics on the Table" looks excellent ...
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1answer
53 views
How to use a fitted model parameters for forecasting other time series
I have fitted a ARIMA(1,1,2) to time series TS1 as below:
arima112<-arima(TS1, c(1,1,2))
now I want to use the coefficients of ar and ma that I got from ...
0
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0answers
57 views
TIme series analysis: ARCH-LM statstics and length of a time series
I have four 30-year long time series of daily correlated weather variables. I estimated a VAR model to the series using vars R package. Then, I executed seriality and normality test on VAR residuals, ...
1
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2answers
143 views
Does R predict or forecast on an arimax model?
I have some data which i am trying to work on. I am pretty new to R though, but i love R. First, I fit an arima model to this data and used the ...
3
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1answer
96 views
Why don't we look at $R^2$ when fitting an autoregressive model?
$R^2$ measures explained variance. In an autoregressive model like AR(k), we are carrying out a linear regression, and as such we would have an $R^2$ and an ...
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1answer
59 views
Autoregression model with a time trend term. Statistically valid?
Assume we have a time-series with a deterministic trend.
I'm wondering if the following model is well specified as an AR model:
$y_{t} = b_{0} + b_{1}t + b_{2}y_{t-1} + \epsilon_{t} \ \ \ \ \ \ $
...
