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

learn more… | top users | synonyms

1
vote
0answers
22 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
46 views

How can one say if a model is poor based on RMSE value

I have a general question about the value of using RMSE to see if a forecasting model is poor. I used the forecast package in R to find forecasting models for ...
0
votes
0answers
8 views

Use cases for P-Kernel for SVMs

I've been reading the book by Cristianini on Kernels (2004) where generative kernels (like p-kernel and fisher-kernel, not to be confused with polynomial kernel!) are described. I am interested in ...
0
votes
1answer
30 views

What statistical analyses should one perform on ensemble forecasts (given a measurement)?

I have an ensemble of time-series predicting a scalar variable. Additionally, I have a measurement time series of this scalar variable. Which statistical analyses could and/or should I perform to ...
5
votes
5answers
130 views

How to characterize abrupt change?

This question may be too basic. For a temporal trend of a data, I would like to find out the point where "abrupt" change happens. For example, in the first figure shown below, I would like to find out ...
5
votes
0answers
245 views

How to find the functional form of pdf from time series using Kernel density estimate

I will appreciate help in determining the functional form of the probability density function (pdf) for the following case. I have read about Kernel Density Estimate for the case when we don't have ...
0
votes
0answers
25 views

prediction for data including weekly and annually seasonality and dummy variables for holidays

I have a three years of daily data for number of orders a trucking company receives everyday. Number of orders are high during weekdays and they have a huge decrease for weekend. I used msts to ...
1
vote
1answer
42 views

prediction using historic data with unusual annual trends

I have 4 years of daily data. there is a decreasing trend for the data for the first 3 years but the trend increase for the 4th year. I wanted to find a fitted model using the first 3 years and then ...
1
vote
2answers
261 views

Wrong predictions for weekend, but good predictions for weekdays

I have a set of 3 years of daily data. I saw weekly and annual seasonality in the data so I used msts time series and tbats ...
0
votes
0answers
37 views

predicting time series with support vector machine using R

I am planning to do time series prediction using support vector Machine. I could not find any materials about time series application of support vector machines using R or Mat-lab. Similar question ...
1
vote
1answer
76 views

Time series forecasting accuracy measures: MAPE and MASE

We come to this toy example showing MAPE and MASE are not consistent when measuring forecasting accuracy. Data consist of 100 white noise and 100 $AR(1)$ time series with length $N=500$, mean $\mu=1$ ...
2
votes
0answers
17 views

Normalized RMSE

I have several time-series in a VAR(1) and, due to some of them haven't the same unit of measure, I'd like to estimate the RMSE in percentage. I know that it could be done in several ways (see below) ...
1
vote
0answers
69 views

Stock closing price forecasting using ARIMA model in R

I have downloaded the daily stock Adjusted Close price of one stock from sep 2011 to till date. As per my study plan, I have plotted some basic plots to understand the daily stock Adjusted closing ...
0
votes
1answer
30 views

Standard model for time series with (possibly multiple) seasonal component

Suppose you have a "new" way to formalize a seasonal component and you want to see if your method is worth to be published. My idea is to take a "standard" model for time series with seasonal ...
3
votes
3answers
80 views

Does Stationarity for Time Series extend to Independent Variables?

There have been many questions about the importance of stationarity and also its means of calculation here on CV, but one question that I have not seen an answer to is whether or not stationarity (in ...
0
votes
1answer
28 views

Data with weekly and annually seasonality but the first day in time series is not the begining of a week

I know it might look naive but I have a very basic question. I have a three years of historic data which has weekly and annual seasonality. January first as my first data is on Wednesday so my time ...
0
votes
0answers
8 views

regression test or two bloc PLS model to prove a gene expression matrix relationship

I have two gene expression matrices, matrix A coming from a set of two hypothetically different cells while matrix B is coming (for certain) from only one of them. The structure of a gene expression ...
0
votes
1answer
41 views

Detecting a step change in time ordered data

Suppose I have data which looks like this: ...
0
votes
2answers
45 views

Problem in ARIMA Model in R

I am running ARIMA model in R and I used auto.arima(X) function to decide appropriate model.After using this function I found that the order of my model is ARIMA(2,1,0). The problem is I run the same ...
3
votes
1answer
53 views

Difference between the forecast and simulate functions in the {forecast} package in R

I have been using the forecast package in R to make forecasts based on an ARIMA model and have noticed a difference in the output of the forecast and simulate functions when calculating confidence ...
1
vote
1answer
45 views

No fitted ARIMA model

I wanted to fit an ARIMA model to a daily database for three years but auto.arima couldn't find a model and showed the following error: ...
0
votes
0answers
12 views

Design study choice for multivariate time series data

I am involved in a research project in which we have data about students and their learning activities. We have two courses C1 and C2 and in each course students communicated using some of the three ...
0
votes
1answer
68 views

Validate a Markov Chain with few states (model switching)

Suppose I have a five state Markov chain. The states are observable (in fact I defined them, they are outcomes of an classification algorithm). So I have a long time series, see the first picture. ...
2
votes
1answer
23 views

Metrics to compare time series results with no defined truth standard

I have several (~10) models which all predict time series results for a specific problem (hourly heat loss from a building over a year). I do not have any measured data or truth standard results to ...
2
votes
1answer
113 views

Forecasting a seasonal time series in R

Forecasting airline passengers seasonal time series using auto arima Hi, I am trying to model some airline data in an attempt to provide an accurate monthly forecast for June-December this year using ...
0
votes
0answers
17 views

what is the best prediction interval for a forecasting model with daily and annually seasonalitis?

If we have a data set which has daily and annually seasonality, is it reasonable to use the forecasting model for one year ahead? I mean, I want to have a 48 hours forecast for a logistic provider ...
0
votes
0answers
34 views

Creating auto arima for two following time series with two different non linear slopes

I'm trying to model (and predict) the following time series, which consist of two periods (enrollment period and non enrollment) as the following: I believe that this model should consist of two ...
0
votes
0answers
15 views

model specification for SARIMA order (2,1,2)x(0,1,1) period 12 [duplicate]

Good morning scholars. Please am fitting a Seasonal Arima model of this form: (2,1,2)x(0,1,1) period 12 but I don't know how will look like. Can anybody help me wit the model specification? Thanks.
0
votes
0answers
39 views

Fitting ARIMAX with lagged X variable (Matlab)

This question is divided into two parts. I currently have a Y vector with 364 data points (Y) and an exogenous variable (X) with 364 data point. X is a good predictor for Y that I want to pair up ...
0
votes
0answers
24 views

What does a fitted value mean in dshw forecasting package?

I have a double seasonal data. I wrote the following code to find the best fit model and find fitted values: orders <- read.csv("DataForR.csv", header = TRUE), NumOrders <- orders$Orders, ...
1
vote
0answers
32 views

Quantity like correlation

I want to calculate this sort of quantity, $f()$, for my data. $x$ and $y$ are time series. $f$ behaves like a pseudo-correlation, but is different in the sense that even if the values jump up and ...
1
vote
1answer
49 views

Transforming a time series with a negative number

I have been given data to forecast however it has a negative figure within the data which then, when doing a log transformation to make the series stationary, the ARIMA script i have written won't ...
1
vote
1answer
51 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
0answers
35 views

ARIMAX model or ARDL?

I would like to study the impact the advertising of a product on its sales (weekly data for 5 years). As the final aim is to forecast what would be the impact on sales of a change in the advertising ...
1
vote
0answers
25 views

Initiator follower analysis with time series data sets

I am a newbie to this forum. I searched different white papers and codes on google but couldn't find a solution, that's when I registered on this forum.. Please share in case you guys have a idea as ...
0
votes
0answers
24 views

Python module request: Spectral density estimation for multivariate time series

I have worked with scipy.signal.welch and spectrum.pptm to calculate power spectral density with Welch and Multitaper methods. However as far as I can see these functions are meant for one dimensional ...
0
votes
0answers
33 views

Time-series detection algorithm for multi-seasonal data using Python

My data: I have two seasonal patterns in my hourly data... daily and weekly. For example... each day in my dataset has roughly the same shape based on hour of the day. However, certain days like ...
3
votes
1answer
27 views

Is there a method to disentangle multiple lines of data that are intermingled?

I have 3 temperature sensors that record data once a minute. All 3 temperatures have the tuple value (instant, temperature). The problem is, they may come in a random order and thus there's no way to ...
1
vote
1answer
35 views

prediction of polls

Just as an example Scotland has poll to decide whether they need to be independent from UK or not. Here is BBC's summary of different polls: ...
0
votes
0answers
4 views

Choose best time window to count events in order to produce an indicator

We want to create indicators for event based clinical conditions, like migraine or epilepsy. This conditions are characterized by events which can happen with various frequencies and we would like to ...
1
vote
1answer
40 views

Residual Value Prediction For Used Electronic Products

I am trying to predict the long term residual value of a product with only the releasing price. I have collected some data off the Internet related with one phone type, and it is pretty obvious that ...
5
votes
2answers
206 views

Average and standard deviation of timestamps (time wraps around at midnight)

I have lots of sensor data with timestamps like "2014-09-09 16:10:45" and accompanying sensor readings. To get some insight into these I want to find "unusual" events by looking at the average and ...
0
votes
0answers
14 views

Calculate standard error in state space model in R

I am estimating a DFM in state space form in R. I have used the function spg from the package BB (optim was not working) and dlm to optimize so now I have the parameters of the filter. I now would ...
0
votes
4answers
210 views

Forecast accuracy calculation

We are using STL (R implementation) for forecasting time series data. Every day we run daily forecasts. We would like to compare forecast values with real values and identify average deviation. For ...
0
votes
0answers
11 views

Sample autocovariance non negative definite

Let $\hat{\Gamma}_k$ be the k dimensional sample autocovariance matrix. I am trying to prove this is nonnegative definite. The first step in the proof is to show that if $\hat{\Gamma}_m$ is ...
6
votes
2answers
212 views

Test to distinguish periodic from almost periodic data

Suppose I have some unknown function $f$ with domain $ℝ$, which I know to fulfill some reasonable conditions like continuity. I know the exact values of $f$ (because the data comes from a simulation) ...
0
votes
0answers
30 views

Predicting one daily variable from another in SPSS

Note: There are similar questions to this one, but they don't seem to get at quite what I'm trying to figure out. I have a week's worth of daily data with a number of variables, including nighttime ...
2
votes
1answer
59 views

standard errors of the fitted values of a time series regression

I really want to understand how the math is working here. I am trying to get the standard error of the fitted values for a time series regression model.In the non-time series regression,I know I can ...
3
votes
1answer
90 views

Unable to understand derivation of Expectation Maximizaton

In Paper, System Identification using Symbolic Chaotic Sequence, Authored by A. Kurian and H. Leung download link under section II B, can somebody please explain ...
0
votes
0answers
55 views

Matlab: Unable to plot partial autocorrelation plot

For a time series I wanted to plot separately the partial auto correlation. Below is the graph for a time series which shows PACF plot of the time series $x$ which I wanted to reproduce: This ...