the political democracies have the different functions that some of them, like governmental change and legitimacy provision of political system are apparent. the mentioned phenomenon furthermore on direction of regime endure has also latent function. so this paper argues that political democracies have a preventive role concerning emergence of political revolutions and violent change of authori...

Recently, the call to combine land change science (LCS) and political ecology (PE) in the study of human-environment interactions has been widely discussed by scientists from both subfields of geography. In this paper, we use a hybrid ecology framework to examine the effects of conservation policies on the environment and the livelihood of the people of the Korup National Park (KNP). Using tech...

A partial least squares regression is proposed for estimating the function-on-function model where a functional response and multiple predictors consist of random curves with quadratic interaction effects. The direct estimation usually an ill-posed problem. To overcome this difficulty, in practice, data that belong to infinite-dimensional space are generally projected into finite-dimensional ba...

People employ the function-on-function regression to model relationship between two stochastic processes. Fitting this model, widely used strategies include functional partial least squares algorithms which typically require iterative eigen-decomposition. Here we introduce a route of based upon Krylov subspace. Our can be expressed in forms equivalent each other exact arithmetic: One is non-ite...

The function-on-function linear regression model in which the response and predictors consist of random curves has become a general framework to investigate relationship between functional predictors. Existing methods estimate parameters may be sensitive outlying observations, common empirical applications. In addition, these severely affected by such leading undesirable estimation prediction r...

Regression via ordinary least squares (OLS) is a commonly applied statistical technique in political science. However, when the dependent variable is dichotomous (0-1) rather than continuous, ordinary least squares becomes an inefficient estimation technique, and the underlying linear probability model (LPM) that is being estimated represents a poor apriori choice of model specification (Aldric...