A Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. It is named after the Russian mathematician Andrey Markov.

In case of Linear Models, we assume a linear relationship between the mean of the response variable and a set of explanatory variables with inference assuming that response variable has a Normal conditional distribution with constant variance. The Generalized Linear Model permits the distribution for the Response Variable other than the normal and permits modeling of non-linear functions of the mean. Linear models are special case of GLM.

Introduction

Introduction

I have always found TCP congestion control algorithms fascinating, and at the same time, I know very little about them. As an engineer working on the roads, it’s essential to understand the traffic requirement and service levels. Similarly, It’s good to understand the transport behavior riding our networks. Once in a while, I will feel guilty about it and spend time on the topic with the hope of gaining some new insights.