Regional archaeological survey involves identifying archaeological traces and sites that can provide a good picture about inter and extra cultural relationships in the region. However, systematic sampling involves dividing the survey area into a sampling frame that gives us details data and information from the sit. Since the Khorasan area is poorly studied in the prehistoric period, we chose Tappeh Borj which is located near Nishapur for stratified systematic sampling in order to get better understanding about cultural and archaeological characteristics on the site and the region. In the following we will mention the results of typology and classification of archaeological findings. Based on the archaeological evidence, we would argue that there was a local culture in the site because there is no significant correlation with neighboring areas.

In this paper, we have proposed an estimator of finite population mean in stratified random sampling. The expressions for the bias and mean square error of the proposed estimator are obtained up to the first order of approximation. It is found that the proposed estimator is more efficient than the traditional mean, ratio, exponential, regression, Shabbir and Gupta (in Commun Stat Theory Method 40: 199– 212, 2011) and Khan et al. (in Pak J Stat 31: 353– 362, 2015) estimators. We have utilized four natural and four artificial data sets under stratified random sampling scheme for assessing the performance of all the estimators considered here.

This article introduces a dual problem of widely used calibration ratio-type estimators for estimating population mean of the study variable considering auxiliary information under dual constraints using stratified systematic sampling design. Under large sample approximations, the expression for bias and variance of the proposed estimator are derived. In addition, the optimality condition for the proposed estimator and hence optimum variance expression is also obtained for the same. Moreover, a study based on real-life data is carried out to judge the performance of the proposed calibration estimator in terms of minimum relative bias and relative root mean squared error criterion. The study reveals that the calibration ratio-type estimator under dual constraints may be preferred in practice as it provides consistent and more precise parameter estimates.

We assessed the accuracy of two sampling methods by comparing their estimations to Full Calipering (FC). The two methods included 1000-m2 systematic random (SR) sampling plots designed within a 150×200 m grid, and a cluster sampling (CS) method with 7500-m2 clusters each embracing 4 plots of 1875 m2 each. Full calipering was performed in 4 parcels of 116 ha each. The inventory resulted in total 40239 trees measured in 40 SR plots (sampling intensity=9.7%) as well as 56 plots within 14 clusters of in CS approach (sampling intensity=3.44%). Results from CS method were associated with optimum accuracy for tree density and forest structure. The CS method returned results closer to the FC when estimating the beech- and hornbeam-specific no. of trees per ha and their distribution in diameter classes and in parcels. The Maximum trees diameter of 165, 110 and 125 cm were recorded for FC, SR and CS approaches, respectively. Conclusively, this study suggests a forest type and species-specific stratification to be performed prior to each parcel-based inventory. In addition, sample size should be determined on a forest type-specific basis, ideally distributed within a CS design with 1900 to 2000-m2 plot sizes.

We extend the method of adaptive two-stage sequential sampling to include designs where there is more than one criteria used in deciding on the allocation of additional sampling e ort.These criteria, or conditions, can be a measure of the target population, or a measure of some related population. We develop Murthy estimator for the design that is unbiased estimators for the population mean, and propose another, more efficient, estimator. We investigate asymptotic properties of this estimator. We use a simulation study to investigate design properties of the multi-criteria adaptive stratified sequential sampling scheme and also some estimator properties under the design.

This study proposes optional Randomized Response Technique (RRT) models in a binary response situation. The application of the proposed optional RRT models under strati cation is also explored. Gupta et al. [1] introduced an ingenious idea of optional RRT model in which a question may appear sensitive to one respondent while being not sensitive to another. This study focuses on estimating  , the prevalence of sensitive attribute,! , the sensitivity level of the underlying sensitive question when the proportion of unrelated innocuous attribute  x is unknown. A new multi-question approach is proposed for estimation of parameters ( ; ! ). A comparison between the proposed optional RRT models and the corresponding full RRT models is carried out numerically under simple and strati ed random sampling.

Background: Traditional survey methods may cause refusals to respond or untruthful replies when encounter the sensitive questions. The Randomized Response Technique (RRT) is designed to decrease social desirability bias and obtain reliable estimates. This study aimed to apply these new methods on the sensitive questions survey.Methods: Simmons model was applied in the survey of issues relevant to commercial sex among men who have sex with men (MSM) in Beijing, China. Stratified two-stage sampling and stratified random sampling were applied.Results: During July to December 2010 in Beijing, the commercial sex proportion among MSM was 0.051 (95% CI: 0.017, 0.085), its estimated variance was 3.01´10-4. The last male condom use rate during commercial sex was 0.778 (95% CI: 0.746, 0.810), its estimated variance was 2.6´10-4.Conclusion: We have introduced new approaches for the sensitive question survey among MSM. The new approaches are proved to be reliable and valid.

In this study, three classes of generalized and more efficient combined regression-cum-ratio estimators are presented to estimate the population mean of the study variable in stratified two-phase sampling considering non-response and measurement error are present jointly. The expressions for the bias and mean square error of the three proposed generalized combined regression-cum-ratio estimators have been obtained. Optimal conditions which make the proposed generalized regression-cum-ratio estimators more efficient than modified combined regression estimator are discussed. The performance of the proposed generalized combined regression-cum-ratio estimators has been compared theoretically as well as empirically with various combined type estimators in stratified two-phase sampling including usual combined ratio estimator, usual combined exponential ratio estimator, usual combined regression estimator, and modified combined regression estimator. An empirical study shows that the proposed generalized combined regression-cum-ratio estimators perform more efficiently than all combined type ratio, exponential ratio, and regression estimators discussed in the study.

2Drought is among the most costly weather-related events and Iran is highly vulnerable to the economic, social and environmental impacts of drought In this study expected profit maximization model and utility efficient programming were applied to determine optimal crop pattern, expected gross margin and water use with and without, drought condition at representative farms of homogenous groups. This study was based on two databases. A sample of 180 farmers was selected for interview and collected necessary farm level data in 2007. The sample farms were drawn using two-stage stratified random sampling method. Results indicated that the largest reduction in expected profit is directed toward farmers who use surface water from river or canal. These groups of farms ultimately suffered a severe reduction in expected income (53%-64%) as a consequence of the drought, largely because their access to water was cut substantially. The least quantity of damage is directed toward homogenous groups of farms that use groundwater or conjunctive use of groundwater and surface water. Reduction in expected income of these groups is equal to 7 and 32 percent of expected income in the normal year, respectively. Finally, the results showed that the pattern of release water from gate of Drodzan have not been optimal in the planting years 2001-2002 and 2006-2007 based on the calculated shadow price of each cubic meter water in different deciles of year.