Parameter Estimation Methods Under Different Graph Sampling Schemes

The world is surrounded by numerous events of certainty and uncertainty, the proportion of later is much higher than the farmer. A moving train can not stop between two stations at equal time intervals on all the days; gun shooter can not repeat the same performance at every occasion; a cricketer is not suppose to hit century in every match. All these are associated with the phenomena of uncertain events and effected by many random inherent causes. A person may think of obtaining average estimate of the inter-arrival time interval of recurring events or may be to compute average performance of a player under uncertainty considerations. Other way to look into an estimation problem in efficient way is by the use of some known observations. Suppose a student is searching a house of his friend in a new city, he cannot perform search without having a few information, in his hand, about the neighbouring of friends house. If this source of additional information is large in amount, the search is easier and faster. While in a city, the proportion of smokers is to be estimated, a sample of some of persons may help to achieve this goal but error occurs due to sample being a small group of population units. If similar estimates of past years are also available, then could be utilized to improve upon the reliability of estimates. One more dimension of the estimation problem is to look into like average income estimation of the people of a community living in the slum area. Data of their expenditure may play an important role to get efficient estimates of this unknown parameter.