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

State Space models with Short Time Series

My problem is that I have a state space model that I estimate using the Berndt–Hall–Hall–Hausman (BHHH) algorithm. The state space model is relatively simple in that the hidden part follows a pure ...
0
votes
0answers
38 views

Four tricky time series questions with a “seasonal twist”

A ski-hotel has the most guests in the third quarter in every year (check the data below after the four questions). Can you answer these four questions (every year has 4 values, the first is quarter ...
0
votes
0answers
19 views

Reproducing ARIMA error terms

When forecasting a moving average (MA) model using R's forecast, why does using residuals(fit) produce different results than ...
0
votes
0answers
14 views

What does it mean intuitively to say that a time series process is causal ?

What does it mean intuitively to say that a time series process is causal ? And what is the relationship between causality and stationary and invertibility ? If I understand correctly, these 3 ...
0
votes
0answers
12 views

How to handle large .csv file in R? [migrated]

I have a large(>100,000) single column floating point time-series data. I want to find structural changes within the data with respect to time( in my case index). In-order to do that, I am using R ...
2
votes
1answer
14 views

Using Yule Walker equations for ACF and PACF

When using Using Yule Walker equations for getting ACF and PACF, is it essential that the time series has to be stationary? In other words, do we really need Box-Cox transformations before we use Yule ...
0
votes
1answer
33 views

How do I replicate these simple state space models from Commandeur's book in Stata?

I'm working through the book An introduction to state space time series analysis by Commandeur and Koopman, and I want to replicate a few of the simple models in Stata 13.1. The two related models I'm ...
0
votes
0answers
12 views

Stream classification of time series

I have a set of time series $\mathcal{Y}$, and a test time series $T$ for which I need to find the closest matching time series $Y_i \in \mathcal{Y}$. This has to be done online, i.e., $T$ is a stream ...
0
votes
0answers
12 views

using decompose function for high frequency data

I have a table as Date Time Energy 1/1/2008 10:30 0.89 1/1/2008 11:30 0.76 and so on. The data is recorded for every half an hour. I wish to ...
0
votes
0answers
11 views

Time series Data Analysis and Forecasting by country and time factor

cty year qtr tl Argentina 2009 Q4 3 Argentina 2010 Q1 2 Argentina 2010 Q2 7 Argentina 2010 Q3 7 Argentina 2010 Q4 10 Argentina 2011 Q1 7 Argentina 2011 Q2 7 Argentina 2011 Q3 1 Argentina 2011 ...
0
votes
0answers
8 views

Model validation and verification for Markov Chain switching model

Assuming I have a discrete-time Markov chain with only five states. The chain will be used for the prediction of the macroscopic states which are observable and coming from a timeseries. I use maximum ...
1
vote
0answers
10 views

Homogeneity of variance for time variable

I have four groups of plant treated with different temperatures and I conducted repeated measurement on their growth rate. I use ANOVA with Mixed Model to analyze the data by specifying both ...
0
votes
0answers
16 views

Are time series variances additive? [on hold]

If I have two variance measurements over two time series $X_1$ and $X_2$ over $t_1$ and $t_2$ respectively, and want to look at it as one variance, is the variance additive? If $S_1$ is variance for ...
1
vote
0answers
16 views

Ensemble model performs better with worse performing consitutent models?

I have a forecast model I am developing that uses some very unreliable input data, missing data (due to sensors or comms failures) is the rule, not an exception. The quantity being forecast is a daily ...
0
votes
0answers
11 views

Weighted average of a time series

I am trying to construct an average from a set of points (time series) considering that the more recent points have a bigger weight. I already tried with the formula of exponential moving average ...
4
votes
1answer
63 views

Does an exponential model fit my data?

I am measuring accumulation of a fluorescent-tagged protein at a particular location within a cell over time. In previous experiments that I have performed, I see a standard exponential distribution ...
2
votes
0answers
20 views

Interpretation of the partial autocorrelation function for a pure MA process

I have been working with some time-series theory and I noticed something that I can understand "mathematically", but not based on the intuitive explanations of what the partial auto-correlation ...
0
votes
0answers
14 views

Seasonal vs non-seasonal coefficients in R ARIMA

Let's say I have the two following ARIMA models: ARIMA(7,1,1) (no seasonality) ARIMA(6,1,1)(1,0,0)7 (seasonality of period 7). Are they conceptually the same? If so, why is that when I model ...
0
votes
0answers
18 views

Average Growth Rate for Year 1 across 5 groups

I have a question that pertains to time series or more likely pertains just to simple math. Lets suppose that I am measuring the number of online visitors to 5 websites on a monthly basis, so I have ...
1
vote
1answer
20 views

Is it possible to measure the independent variable with part of the dependent variable

I have Beta as my independent variable and Economic value added (EVA) as my dependent variable. To calculate EVA I need to use Cost of capital and to calculate that I have to use Beta, so is it ...
1
vote
1answer
28 views

Time Series Cross Sectional Analysis and Forecasting With R

cty time tl Argentina 2009_Q4 3 Argentina 2010_Q1 2 Argentina 2010_Q2 7 Argentina 2010_Q3 7 Argentina 2010_Q4 10 Argentina 2011_Q1 7 Argentina 2011_Q2 7 Argentina ...
-1
votes
0answers
37 views

Sales Forecasting using Support Vector Machine

I have sales data for last three years 2011-2013. I want to use Support Vector Machine technique in R to do the predictions. I just wanted to know that the approach that I am using is correct or not? ...
0
votes
0answers
23 views

How to interpret residual plots from time series regression

I am doing a time series regression between 2 variables. I used the dynlm library in R. I'm trying to understand how to interpret the results. Could you please point out where I am getting it wrong: ...
0
votes
0answers
42 views

The best way to solve particular classification problem?

I got training set (time series) of size approximately 2 million precedents {x,y}. Each x is a vector of size 20 and each y is a binary vector of size 10 like {1,0,0,1,1,0,1,1,1,0}. For a new input x ...
2
votes
1answer
47 views

Consistency of OLS in presence of deterministic trend

For consistency of OLS estimator for linear model $$ y_i = \beta^T x_i + \epsilon_i, \; i = 1,\cdots, n, $$ the model assumptions are usually (the ones I am familiar with) The sequence of random ...
0
votes
0answers
30 views

What types of statistical analysis technique available to compare two different time series [closed]

I am currently looking for suggestion to compare or study the two different period time series like sales in 2000 and 2001. As it is sales of the same product and i would like to compare those two ...
0
votes
0answers
24 views

Identify the stationary time series

Identify the stationary time series for which $$ \gamma(h) =(-1)^{|h|}+\cos \left(\frac{\pi}{4}h\right)$$ is ACVF. This is a homework problem. Stuck at first level. Please give some hints. Thanks in ...
1
vote
1answer
21 views

Comparing polynomials

I've got a bunch of data on pop singers' performance on the Hot 100 charts over time, and I'm trying to compare the early part of different artists' careers. For example, I might look compare Miley ...
1
vote
1answer
11 views

Holt-Winters and Abnormal termination in LNSRCH

I try to fit data with Holt-Winters function in R. Nevertheless, i am getting the following message: ...
0
votes
0answers
21 views

breakpoint analyses on multiple series: how to detect common points

I have 20 time series that span the same period (100 days each), from 4 species sampled at 5 different location. I made a loop to perform a breakpoint analysis on all of them, resulting in 0 to 3 ...
0
votes
1answer
16 views

How to blend multiple time series models?

I have three different linear, multi-variate time series models with a best fit against the same observed value $Y$ at 1 minute, 3 minutes and 10 minutes horizons respectively. Each model is using ...
0
votes
1answer
27 views

Hodrick-Prescott derivation in lay terms

I am currently working with the Hodrick-Prescott filter. I would like to understand the equation in lay terms.
3
votes
1answer
31 views

Spread-Level Plot versus Power Transformation Functions in R

I'm having trouble interpreting the results from the Spread-Level Plot function in R (car package). The documentation says: PowerTransformation spread-stabilizing power transformation, ...
0
votes
0answers
14 views

How to down weight correlations in my microarray analysis?

Background: I have been tasked in one part of my analysis to reproduce a method used in another study as follows in bullet points form: Microarray data from a number of time points Calculate ...
0
votes
1answer
39 views

Why we check the residuals of ARIMA model for white Gaussian?

I have problem about the assumptions and model verification of ARIMA models. I know that Gaussian distributed assumption is not necessary for fitting ARIMA models but I wonder why a lot of people ...
0
votes
0answers
11 views

Autoregressive model with input variables in proc arima procedure

I am currently working on the time series analysis for series Y but I have to use other two variable A and B as an input variable in SAS proc arima procedure. But I am unable to interpret the cross ...
0
votes
1answer
18 views

How do I combine multiple time series models to create a generalizable predictive model?

I have several time series that are each observations of the same phenomenon, for example: Observation 1: 10, 25, 36, 72, 80, .... Observation 2: 32, 46, 78, 90, 100, .... Observation 3: ...
1
vote
1answer
23 views

Cosinor analysis with repeated cycles

I'm interested in developing a model for the circadian rhythm of hormone levels via a cosinor analysis. I just started looking into cosinor analyses so I have a few questions. The data is being ...
1
vote
2answers
42 views

How to stationarize profit and loss data with an increasing variance and large negative values for time series analysis?

PnL can take large negative values, and its variance increases over time as the firm grows. If we do differencing, an increasing variance remains. If we take log, negative values cannot be defined. ...
0
votes
0answers
10 views

Timeseries analysis for increase of database memory usage over time [closed]

Hi I have data that shows memory used/increased over time in terms of GBs. Now I have data something like shown below: Db1,25gb Db2,50gb And so on I have few ...
0
votes
0answers
3 views

R-package dlm (dynamic regression, dlmRegMod), especially CAPMDLM example… please help me! [migrated]

I am a graduate student in Business. Fortunately, I found a DLMCAPM code (https://github.com/VSRonin/DLMCAPM/blob/master/Final%20Work.R) for a bivariate case in GitHub regarding on the Dynamic ...
0
votes
1answer
15 views

How to use a set attributes of an entity at different time snaps to make predictive analysis?

The problem is to come up with a classifier for any task based on a set of attributes of an entity having different values at different times. For instance think about football players and their match ...
0
votes
0answers
39 views

How to perform multilevel interaction [on hold]

Which model is correct and can be applied? $$Y=x_{1} + x_{2} + \left(x_{1}x_{2}2013\right)+ \varepsilon$$ $$Y=x_{1} + x_{2} + \left(x_{1}2013\right) + \left(x_{1}x_{2}2013\right)+ \varepsilon$$ ...
2
votes
1answer
36 views

how to calculate a summary value and statistical error in time series

I have a set of data that comes for empirical measurements over a number of days. From the beginning of the experiment to the end of it, every five minutes temperature was measured inside (Ti) and ...
0
votes
0answers
12 views

estimating period and dealing with Non negative values in forecasting

When I read time series in a ts object and put a period: 1) tr <- ts(data[,4],frequency=). This works for two different periods and decomposes perfectly to show (downward) trend, seasonality and ...
0
votes
0answers
18 views

Wilcoxon rank sum test for significant differences between two time points

I have data like so …(Col1:Companyname Col2:Data at timepointA; Col3:replicate Data at timepointA; Col4:Data at timepointB; Col5:replicate Data at time point B ...
0
votes
0answers
10 views

Count variable as control variable in regression in SPSS

I'm doing a research on development of audit fees in 2005-2012. I'd like to see if there's a downward or upward trend in them. I have made a count variable of the years (2005=1 2012=8) and now should ...
0
votes
1answer
37 views

A Kalman Filter for estimating z-scores?

I have been struggling to fit the following problem into a linear state space model for a Kalman Filter (KF). I'm having a hard time seeing what I'm doing wrong. I suspect I'm violating some law of KF ...
1
vote
2answers
49 views

Time series - correlation and lag time

I am studying the correlation between a set of input variables and a response variable, price. These are all in time series. 1) Is it necessary that I smooth out the curve where the input variable is ...
0
votes
0answers
13 views

How to calculate confidence interval for difference (or ratio) of two different time series?

I have two time series which are sampled at the exact same times. I would like to calculate a confidence interval either for the ratio between the two or the difference between the two. The values ...