Time series data has memory. It remembers what happened in the past and avenge any wrongdoings! Can you believe it? Okay the avenging part may not be true, but it definitely remembers the past. The “memory” refers to how strongly the past can influence the future in a given time series variable. If it has a strong memory, then we know that analyzing the past would be really useful to us because it can tell us what’s going to happen in the future. If you need a quick refresher, you can check out my blog post where I talked about memory in time series data. We have a high level understanding of how we can classify time series data into short memory and long memory, but how do we actually measure the memory? Continue reading

# Category Archives: Mathematics

# What Is Pareto Optimality

Let’s consider a business deal where there are multiple parties negotiating the terms. In such a situation, it’s usually not possible for every single party to get everything it wants. They need to optimize their demands so that everyone comes out with something positive. Similar situations arise across many areas of engineering where we have to deal with many resources and we need to make a trade off based on cost, quality, speed, and so on. How do we model this problem and decide the optimal state of affairs? This is where the concept of Pareto Optimality comes into picture. Continue reading

# What Is Long Memory In Time Series Analysis

We encounter time series data very frequently in the real world. Some common examples include real time sensors, surveillance video, stock market, astrophysics, speech recognition, and so on. In order to study time series data, we try to extract various characteristics that tend to define it. One of the most important things to think about is the dependence between various points in the time series data. Is there any dependence between the values in the time series data? If so, how far apart in time do they have to be in order to affect each other? Understanding these aspects will open up new doors in terms of how we analyze the data. This is where the concept of long memory comes into picture. Let’s dig a little deeper and understand it, shall we? Continue reading

# Estimating The Predictability Of Time Series Data – Part II

In the previous blog post, we discussed various types of time series data. We understood the concepts of stationarity and shocks. In this blog post, we will continue to discuss how we can estimate the predictability of time series data. People say that future is unpredictable. But that’s grossly reductive! What they actually mean to say is — I’m blindly assuming that my time series data is non-stationary, so I cannot accurately predict what’s going to happen in the future. Predicting future values can open a lot of doors in the Internet of Things (IoT) ecosystem. Before we can forecast future values, it’s important to determine if the time series data exhibits any properties that can be modeled. If not, we are just dealing with chaos and no model will be good enough. But a lot of data in the real world exhibits patterns, so we just need to look at it the right way. Let’s see how we can check if the given time series data has any underlying trends, shall we? Continue reading

# Estimating The Predictability Of Time Series Data – Part I

Time series data refers to a sequence of measurements made over time. The frequency of these measurements are usually fixed, say once every second or once every hour. We encounter time series data in a variety of scenarios in the real world. Some examples include stock market data, sensor data, speech data, and so on. People like to build forecasting models for time series data. This is very relevant in modeling data in the world of Internet of Things (IoT). Based on the past data, they want to predict what’s going to happen in the future. Once of the most important questions is to see whether or not we can predict something in the first place. How do we determine that? How do we check if there are underlying patterns in the time series data? Continue reading

# Underlying Pattern Governing The Prime Divisors

When we think of prime numbers, the first thing that we tend to associate them with is randomness. Prime numbers are scattered all over the number line and there is no fixed formula that can tell you when the next one is going to occur. This has been used heavily by mathematicians and cryptographers to develop security systems for internet, banking, communication, and so on. Coming to the topic at hand, we are going to talk about prime divisors of a given number. Prime divisors of a number are divisors of that number that happen to be prime numbers. Big surprise, right? Alright, what’s so interesting about them? Continue reading

# The Interesting Case Of Russell’s Paradox

The picture on the left is actually a joke related the topic of discussion here. It’ll make sense soon! Russian Dolls, also known as Matryoshka Dolls, are wooden dolls that are placed inside one another. You can read more about them here. Back in the late 1800s, Set Theory was really picking up pace and mathematicians were getting really intrigued by this field. They were devotedly working towards formalizing this field of study. The problem was that there were many loose definitions floating around and there wasn’t any concrete work towards formalizing it. It all started when naive set theory was being used to discuss the foundation of mathematics. Instead of describing set theory with formal logic, people were describing it informally using words. So why should we care about that? What’s wrong with using words to describe set theory? Continue reading