One problem may owe to the inappropriate way of splitting sub-period. The Chow test assumes there is a known break point in the series. If this is not known, the Chow test is not appropriate. We could use the predictive failure test to do the test again to verify the result. Other reasonable approaches include splitting the data according to any obvious structural change in the series showing in the graph or any known important historical events.
Isometric Feature Mapping also known as ISOMAP is often used to solve dimensionality reduction problems. Some of the traditional methods for dimensionality reduction are Principal Component Analysis (PCA) and Multidimensional Scaling (MDS). However, these techniques assume that the data points lie on a linear subspace of the high dimensional input space and cannot be used to capture any inherent non-linearity of the data image. The main advantage of ISOMAP over these linear techniques and other non-linear techniques is that it is capable of efficiently calculating a globally optimal solution. It is possible for two points to be extremely close in the original data as measured by their Euclidean distances but can be extremely far apart in the lower dimensional manifold when measured by the geodesic or shortest path distances.
Without a point by point, taught strategy and methodology, organizations will frequently experience the ill effects of conflictingly connected arrangements and systems, higher dangers and more genuine dangers, and procedures that will be specially appointed as opposed to all around characterized and/or improved. The outcomes will have a tendency to reflect lower proficiency, conflicting supply results, and higher working
Also this study cost to much.Another weakness is Control effects repeated interviewing of the same sample influences their behaviour. Some strengths of cross-sectional study is cheap to administer, and it is quick to conduct. Another, strengths of cross-sectional study is Charts aggregated pattern. Some weakness of cross-sectional study is do not permit analysis of causal relationships. Also, Unable to chart individual variations in development or changes, and their significance.
This is due to the fact that the cases are analysed as a sequence where A leads to B (Sekhon, 2004: 288). On the other hand is a disadvantage of comparative case studies that the entire focus is on a single cause only, which doesn't provide answers if there are possibly more explaining variables (Mahoney, 2007: 135). Furthermore is it less transparent and formalized than the other two methods I will discuss; qualitative comparative and statistical analysis. Comparative case studies are harder to replicate due to their very nature of being unique cases (Blatter & Haverland, 2012: 67; Benoît Rihoux & Ragin, 2009: 14). Which is also the cause for the last disadvantages; uniqueness of the cases leads to a lower degree of generalization of any conclusions drawn in comparison to statistical analysis (Blatter & Haverland, 2012:
The idea that one’s own issues take priority over the other sides’ and can therefore lead to a result in the negotiations which are less satisfactory for both sides. When one’s own issues are most important there can be a miscommunication and it can lead to one overestimating or underestimating the importance of issues based on the importance to them. The other theory is one called the ‘Fixed-Pie Belief’, the assumption that if one side gains it is at the other sides’ expense. These are the theories which the authors hope to answer with the aid of this
So, if there is a prehistory of conflict among stakeholders, then collaborative governance is improbable to succeed unless (a) there is a high degree of interdependence among the stakeholders or (b) positive steps are taken to remedy the low levels of trust and social capital among the stakeholders. Interdependence: when stakeholders are unable to fulfill something on their own, is a broadly recognized precondition for collaborative action (Gray, 1989; Thomson & Perry, 2006). The final driver, uncertainty, is a primary challenge for managing social problems (Koppenjan & Klijn, 2004; Rittel &Webber, 1973). Uncertainty that cannot be resolved internally can drive groups to collaborate in order to decrease, distribute, and share risk. Collective uncertainty about how to manage social problems is also related to the driver of interdependence.
Disadvantages of Qualitative method The primary disadvantages related with qualitative methods are at first, the procedure is tedious, and besides, a particular, vital issue could be overlooked. The second potential issue is that a particular issue could go unnoticed. All researchers‟ translations are constrained. As situated subjects, individual experience and information impact the perceptions and conclusions. Additionally, in light of the fact that subjective request is for the most part open-finished, the members have more control over the substance of the information gathered (Yauch and Steudel, 2003: 472-473).
A Gaussian mixture model was proposed by Yamanishi et. al.. Where each data point is given a formulated score and data point which have a high score declared as outlier. Detecting outlier based on the general pattern within data points was proposed by  where it combines a Gaussian mixture model and supervised method Depth based outlier detection  is one of the variant of statistical outlier detection. Depth based outlier detection search outliers at the border of the data space bur independent of statistical distributions.
To be able to run this method it is important to correctly formulate your problem, constraints should affect feasible region otherwise it’s a redundant constraint and should be removed from the problem ( sometimes redundant constrains are hardly recognized until the problem is solved). Linear programming is one of the most popular quantitative methods due to its simplicity in understanding and implementation, provides better quality of decision making, it enables users to solve diverse combination problems and is very adaptive and flexible in terms of analysis, however