# Construction for the useful classes of minimal circular neighbor designs: A comprehensive framework

## TL;DR

This paper introduces a framework for constructing minimal circular neighbor designs to reduce bias in experiments.

## Contribution

The novel contribution is a method using cyclic shifts to generate practical neighbor design classes.

## Key findings

- Cyclic shifts yield sets of shifts for combinations of v and k.
- Constructors simplify generating practical neighbor design classes.
- The framework allows for future development of novel designs.

## Abstract

The primary source of bias in the estimation of treatment effect is neighbor effect which can occur in a variety of experiments. This kind of prejudice is reduced by the usage of neighbor balance designs. This article explains the logic behind developing the constructors by using the method of cyclic shifts, which yields sets of shifts for possible combinations of v and k to generate minimal circular balanced neighbor designs and their generalized classes when the effects of left-neighbor and right-neighbor are equal. These constructors make it simple to create a number of practical neighbor design classes. The process of creating the constructors will serve as the foundation for the researchers to create additional constructors for novel designs with additional crucial characteristics.