0
votes
0answers
25 views

STL-decomposition of a time series with deterministic trend and seasonality

what is the relationship between STL-decomposition and deterministic components of time series like trend or seasonality? I have a time series with deterministic trend and deterministic seasonality, ...
0
votes
0answers
4 views

Using dates in R for Theil-Sen [migrated]

I am trying to use dates as my X variable in a Theil-Sen slope estimation and I am having difficulty using the R package zyp ...
1
vote
1answer
142 views

What if the trend is changed?

I want to forecast tourist arrivals using time series analysis. I expected to use monthly data from 2000-2013. But due to the civil war, the trend was changed after 2008 as in the following plot. ...
5
votes
5answers
129 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 ...
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 ...
2
votes
1answer
30 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 ...
0
votes
1answer
110 views

How to dampen forecast to improve accuracy?

According to Armstrong there is ample empirical evidence that dampening trends in uncertain and complex long term forecasting helps improve accuracy/reduce forecasting errors. What I'm not able to ...
0
votes
1answer
122 views

Difference between series with drift and series with trend

A series with drift can be modeled as $y_t = c + \phi y_{t-1} + \epsilon_t$ where $c$ is the drift(constant), and $\phi=1$ A series with trend can be modeled as $y_t = c + \delta t + \phi y_{t-1} + ...
2
votes
0answers
131 views

Prewhitening time series: ARIMA-modelling versus polynomial trendelimination

I'm concerned with Box-Jenkins-models and especially the first step, the prewhitening to obtain meaningful crosscorrelations for identifying transfer functions and building regression models. I'm ...
0
votes
0answers
35 views

Trend estimation for participation?

I have logs for users and posts in a blog platform for 3 years. I can easily find out how many posts each user have made per day/month/year/etc. What I want to find out is if the frequency of posts ...
0
votes
1answer
61 views

How to find which time series is trending more?

Let us say I have two sets of time varying series as shown below: ...
1
vote
0answers
33 views

What is usefulness of time series decomposition if building a multivariate model?

I am at the early stages of building a panel regression model of sales data. I know my final model dataset will consist of log sales, control variables and log media variables. I am planning to use ...
5
votes
2answers
665 views

R detect increasing/decreasing trend of time series

I have lots of time series with periods: day, week or month. With stl() function or with loess(x ~ y) I can see how trends of ...
0
votes
1answer
215 views

Testing “trends over time” of dummy variables

Let us say this is an output of a model I ran in Stata, where int_retis a continuous variable and time1-...
0
votes
0answers
43 views

Multiple time series methods for trend identification, forecasting etc

I have several time series consisting of aggregated macro-economic indices and I am trying to choose one or several appropriate techniques in order to answer a number of questions. First, I need to ...
1
vote
2answers
352 views

How to test for presence of trend in time series?

Apart from detecting trend from a time series plot, how do you test for its presence before removing the trend using moving average? I fitted a mathematical trend to the data and the slope was ...
0
votes
0answers
28 views

How to test if the mean of data collected over many days is significantly higher on a predicted day

I have some data examining blog posts on different days. Basically, about 2000 news articles pertaining a certain topic were sampled and each blog post was given a positivity percentage score ...
1
vote
0answers
80 views

Trend and seasonality tests for a univariate time series

I am working with a batch of about 1000 univariate time series in R . For every time series, I have to perform following tasks , before deciding upon a model be it ARIMA, TAR or Holt Winter's Model ...
0
votes
1answer
103 views

Trend test on historical stock prices, where to start?

I am a beginner on statistic but come across an urgent situation that I have to work with statistics of stock prices data. I have learned that ones can do a hypothesis test that rejects the Random ...
0
votes
0answers
42 views

Seasonal Data with Yearly “Step” Trend

Trying to plan for upcoming inventory needs for a clothing company. There is a strong seasonal component to the data. At the beginning of the year, sales are up; at the end, sales are down. Each ...
0
votes
0answers
117 views

Forecasting time series with trend and seasonality

I have a univariate time series, which has a trend and month seasonality. Traditionally I have been using auto.arima() method in R to model such series. So when I ...
2
votes
1answer
235 views

Pros and Cons: Methods for Detrending Time Series Data

My memory is fuzzy on the advantages and disadvantages of various methods for detrending time-series data. I'm looking for a succinct summary of why and when one should or should not use the ...
0
votes
1answer
81 views

Power of Seasonal Kendall Trend test

I was asked about doing a power analysis of a seasonal kendall trend test. I feel like that would be really difficult to do and I haven't found any documentation or software on how to do it. Is there ...
1
vote
1answer
207 views

ARIMA with difficult seasonality in R

I have non-stationary time series. It has evident trend in means and seasonality. These raw data are measured every second. On the plot of original series I see trend and seasonality about 80,81 ...
1
vote
3answers
323 views

R - Find curve pattern of simple time series

I have time series data of credit card transaction volumes for different companies. For example: week1: \$5000 week2: \$6000 week3: \$6200 week4: \$7000 week5: \$9000 ... Is there a simple method in ...
0
votes
3answers
182 views

Question about eliminating seasonality

I am trying to remove seasonality from data. I tried the non-linear trend using the code: trend=lm(NH3cH6~t+cos.t+sin.t). The plot was shown as following: However, as you can see, the second peak of ...
0
votes
0answers
55 views

Imputing missing values in a count time series with variable effort with the goal of trend estimation

I have a time series monitoring data set that looks like below: The response is a count. ...
0
votes
3answers
181 views

Deterministic components in covariates/exogenous variables in time series models

Actually, I have read a pair of books about time series analysis, but I am still not sure about how to treat deterministic components, like trend and seasonality, in the exogenous variables in a time ...
1
vote
2answers
386 views

Autocorrelation and trends

What is the relation between the autocorrelation and the trend? Can a trend exist in a time series of independent variables? And in time series with a non-zero autocorrelation, does a trend always ...
1
vote
1answer
97 views

$R^2$ from a regression of two trend-stationary processes, $Y_t$ and $X_t$

In Estimation and Inference in Econometrics, by Davidson and MacKinnon, p.671, they claim that $R^2$ from a regression of $Y_t$ on $X_t$, where both time series are trend stationary, tends to 1 as $n$ ...
0
votes
2answers
118 views

Can time series be used to predict series which has a changing trend?

Supposing I have a stock return series from 2000-2013. Looking at the data, it has pattern of long trending bull market: 2001-2008, and 2010-2013, while it also has great reversal in 2008 financial ...
1
vote
0answers
110 views

Detecting trends in a data stream in real-time

I'm trying to detect trending topics on Twitter in real-time. What I'm doing is every time I get a tweet I assign the tweet to the cluster that talks about the same topic as the tweet. Regardless of ...
0
votes
0answers
111 views

Statistical significance of long term trend?

I have data sets of long term climatology wind speed data on daily basis for 1950-2000. I have calculated the mean for every year and calculated trend pattern, it shows some positive trend of 0.05 ...
2
votes
0answers
331 views

What is the difference between a stochastic and a deterministic trend?

Models with stochastic trends i.e., structural time series models are useful in some instances. Firstly, it may be hard to identify multiple structural breaks in the deterministic trend when the ...
0
votes
1answer
458 views

Detecting a (statistically) significant change in time series trend

Suppose I have two time series (Series1 and Series2) which are identical from timePeriod -200 to timePeriod 0. Say that in timePeriod 0 they are both equal to 100. Series1is equal to 200 at timePeriod ...
1
vote
2answers
191 views

Time-series autocorrelations all positive

I've got 36 months of timeseries data, and eyeballing it, it has a linear trend upward. I wanted to do a little more than just eyeball it though. So I put together a correlogram of autocorrelation ...
1
vote
2answers
193 views

Spotting trends in time based data

I have a dataset which I need to spot trends in. The actual data refers to operation calls which take a certain amount of time to complete. My client wants to know which operation calls are improving ...
3
votes
1answer
239 views

What are the assumptions for checking the stationarity of a time series?

I am checking stationarity or non-stationarity of a time series with R and I am using adf.test and kpss.test in ...
2
votes
1answer
649 views

State Space formulation of Hodrick-Prescott filter

I would like to apply the Kalman filter in order to get a causal Hodrick-Prescott filter. The Hodrick-Prescott filter models a time series $(y_t)_{t=0}^T$ as $$ y_t = \tau_t + c_t $$ where $\tau_t$ is ...
0
votes
0answers
92 views

Combining time series

I need help with time series. In group $A$ I have $N$ time series. These are value features extracted from an EEG (electroencephalograph) signal in each session of treatment. In group $B$ I have ...
1
vote
1answer
115 views

How can I get annual rates of change for combined trend estimates?

I would like to combine trend indices (gained with different methods referring to the same subject, assuming they do not differ significantly) of two different time series and to derive the combined ...
1
vote
2answers
882 views

Detect trend in time series

Hypothesis: time series has an inverted-U shape. How do we test this numerically? My idea is to take the first difference of the variable and fit a linear model using the differentiated variable as ...
1
vote
1answer
108 views

How do I prepare data which has a trend for use in a Copula model?

I want to use a set of daily water quality data including 3 parameters in a Copula model. Somebody told me these data do not have a condition of a random variable to use in copula, and I should do ...
4
votes
1answer
709 views

Criteria to set STL s.window width

Using R to perform STL decomposition, s.window con­trols how rapidly the sea­sonal com­po­nent can change. Small val­ues allow ...
1
vote
1answer
165 views

Trend of a few time points

Suppose we are given a matrix of many rows (different genes for example) and few columns (different time points) and we want to identify the top rows (genes) that are following a trend, like ...
1
vote
0answers
258 views

Thresholds for detection of significant change from baseline in time-series data

I have a data set containing a daily sensor data measurements recorded from 20 participants for 60 days (baseline data). I am trying to develop methods for predicting/estimating decline in long-term ...
5
votes
1answer
439 views

Double exponential smoothing in multivariate multilevel panel regression

I would like to use double exponential smoothing to predict prevalence rates of care dependency in Austrian federal states. My data is very detailed, thus I would like to make use of that in order ...
0
votes
0answers
67 views

When are two trend estimates identical within errors?

Given two linear trend estimates $m_1$, $m_2$, with their respective errors $e_1$, $e_2$, how can I determine if the two trend estimates are the same within errors? EDIT: Both estimates are derived ...
5
votes
0answers
131 views

What's the probability a rabbit will return to a (certain) forest?

Let's assume we have a forest. And there is a breed of rabbits that is visiting that forest all the time. It is possible to distinguish every individual rabbit. There are devices in that forest ...
3
votes
1answer
335 views

How to combine several time series into a useful average time series?

Let's assume we have four time series a, b, c and d with 10 measurments. a(1), ..., a(10) b(1), ..., b(10) c(1), ..., c(10) d(1), ..., d(10) a, b and c are ...