# Search results

1. ### Cross correlation and t tests

I have two time series data from two machines arranged sequentially ( machine 1 output goes is machine 2 input) . I wanted to compare the mean utlisation of these machines and see which one is higher over a given period of time. The two time series data is cross correlated. . So my question is...
2. ### Time series - descriptive statistics

My task is to summarises the descriptive statistics of time series data ( mean, SD , standard error ). It is fairly starightforward for a stationary series. But How do we find out the mean, standard deviation, standard error of the non stationary time series data? I have been reading about the...
3. ### Matt Whiteny U test Vs T test

Hello fellow statisticians, Problem definition: I need to test whether the difference between the "mean" utilization metrics of two machines is statistically significant. Given Data: Utilisation data is available for two machines for more than 100 days. Therefore, the mean, standard...
4. ### time series analysis

There is an aggregated measure represented by a variable A, modeled as a time series from a process. There was a need forecast A and also to find out the historical amount of data of A that is the best reflector of future values of A (as there was a data storage capacity issue). Using a...
5. ### ARIMA

There is an aggregated measure represented by a variable A, modeled as a time series from a process. There was a need forecast A and also to find out the historical amount of data of A that is the best reflector of future values of A (as there was a data storage capacity issue). Using a...
6. ### Which is the better prediction model?

The aim is to predict the breakdown time of a machine as a percentage of scheduled hours for the next day. So my time series looks like this, Break_down_percentage = 7%, 8%, 10%, 6%, 12 % etc. There are 315 data points which can be used to test the different models. I used ets(), arima()...
7. ### updating ARIMA model

When should one use the different types of ARIMA model as mentioned below: Estimate the model order in the training data set and use the same order to forecast future values (updating the parameter estimates) Use a rolling window (e.g. 30 day )to make a new forecast by estimating model order...
8. ### Anova or t-test on squared errors

I have two forecasting models, moving average and single exponential smoothing. The values of Mean Absolute Percentage Error (MAPE) is 5.2%, 5.8%. Since the difference of MAPE between the models are very close, I am quite confused which model to choose. Can we perform a t-test or ANOVA on...
9. ### Models comparison

I have a time series data of 1000 points for each of the different machines. I tried different forecasting techniques to make a one step prediction. The goal is to find out one common predictive model that could work for all machines. The forecasting techniques used are, 5 period moving...
10. ### Linear regression vs logistic regression

I have a time series dataset. The, X (Independent variable) is time and is denoted as 1,2,3,4,5,6..1000.etc Y (Dependent variable ) is a percentage scale as 99%, 98.7%, 96%, 91% ...etc. This is a continuous data set. I have 1000 such data points. The first 700 data points used as training set...
11. ### Prediction Intervals

I am in the process of calculating the prediction intervals on a time series data linear regression model The independent variable in my model is time measured as 1,2,3,4,...,40. I have a dependent variable which is a continuous variable. Now when calculating the prediction intervals using...
12. ### Regression Type Estimation

Hello, Attached is a time series data that has a plot of the percentage of breakdowns on a scheduled hours across the days. The objective is to predict the value for the next day. I tried to use linear regression to fit the data, but got a p-value higher than 0.05 and R square value less than...