On rates of convergence to infinitely divisible laws for dependent random variables

Large O and small o approximations of the expected value of a class of functions (modified K-functional and Lipschitz class) of the normalized partial sums of dependent random variables by the expectation of the corresponding functions of infinitely divisible random variables have been established. As a special case, we have obtained rates of convergence to the Stable Limit Laws and to the Weak Laws of Large Numbers. The technique used is the conditional version of the operator method of Trotter and the Taylor expansion.     

Locally best invariant and locally minimax test of independence

Let X₁ X₂ … X_N be independent normal p-vectors with common mean vector $$ = ($$) and common nonsingular covariance matrix $$ = Diag ($sG_i) [(1–p) I + pE] Diag ($sG_i), $sG_i> 0, i = 1… p, 1>p>=1/p–1. Write r_ij = sample correlation between the i th and the j th variable i j = 1,… p. It has been proved that for testing the hypothesis H₀ : p = 0 against the alternative H₁ : p>0 where $$ and $sG₁,…, $sG_p are unknown, the test which rejects H₀ for large value of $$ r_ij is locally best invariant for every $aL: 0 > $aL > 1 and locally minimax as p $$ 0 in the sense of Giri and Kiefer, 1964, for every $aL: 0 > $aL $$ $aL₀ > 1 where$aL₀ = P_p=0 $$.     

On the Bayesian analysis of categorical data: the problem of nonresponse

It is demonstrated how a suitably chosen prior for the frequency parameters can streamline the Bayesian analysis of categorical data with missing entries due to nonresponse or other causes. The two cases where the data follow the Multinomial or the Hypergeometric model are treated separately. In the first case it is adequate to restrict the prior (for the cell probabilities) to the class of Dirichlet distributions. In the case of the Hypergeometric model it is convenient to select a prior from the class of Dirichlet-Multinomial (DM) distributions. The DM distributions are studied in some details.     

Chinese grand(parenting) encourages a re-imagining of Canada's immigration regime

Canada's migration regime prioritizes the admission of young skilled immigrants while restricting elderly immigrants constructed as non-contributing dependents. We review and compare the current pathways to family reunification for elderly immigrants. Based on interviews with 16 Chinese skilled immigrant mothers and eight sponsored (grand)parents in Edmonton and Ottawa, we highlight the contributions made by elderly Chinese immigrants to social reproduction, intergenerational cultural preservation, and various forms of transnational support. We also reveal the financial and emotional costs incurred by young skilled immigrants who sought to sponsor their elderly parents for permanent residency. Based on these rich conversations, we propose two policy recommendations to reduce the pressure on sponsoring family members and create opportunities for elderly immigrants to access gainful employment.     

Identifiability of distributions under competing risks and complementary risks model

Let X₁,X₂,…,X_p be p random variables with cdf's F₁(x),F₂(x),…,F_p(x)respectively. Let U = min(X₁,X₂,…,X_p) and V = max(X₁,X₂,…,X_p).In this paper we study the problem of uniquely determining and estimating the marginal distributions F₁,F₂,…,F_p given the distribution of U or of V.

First the problem of competing and complementary risks are introduced with examples and the corresponding identification problems are considered when the X₁'s are independently distributed and U(V) is identified, as well as the case when U(V) is not identified. The case when the X₁'s are dependent is considered next. Finally the problem of estimation is considered.     

Hellinger distance as a penalized log likelihood

The present paper studies the minimum Hellinger distance estimator by recasting it as the maximum likelihood estimator in a data driven modification of the model density. In the process, the Hellinger distance itself is expressed as a penalized log likelihood function. The penalty is the sum of the model probabilities over the non-observed values of the sample space. A comparison of the modified model density with the original data provides insights into the robustness of the minimum Hellinger distance estimator. Adjustments of the amount of penalty leads to a class of minimum penalized Hellinger distance estimators, some members of which perform substantially better than the minimum Hellinger distance estimator at the model for small samples, without compromising the robustness properties of the latter.     

Affective politics and reading/writing poetry from the Northeast of India

ABSTRACT

Theorization of cultural and political issues of Northeast of India often creates a disengagement from the actual cultural performances produced in the region. This unique geo-cultural place is sometimes homogenized. In actuality, it is the home of diverse socio-cultural practices and performances. In the context of globalization, deforestation, Christianization, other internal clashes and external influences, material bodies, here, are continuously being rewritten in socio-cultural sphere. Non-representational theory considers poetry as an effective mode of exhibiting the virtual multiplicity of the nonrepresentational world. This paper will focus on exploring the corpus of Northeast Indian English poetry that focuses on social practices and bodily experiences to interpret the entire cultural flow of everyday life. As Non-representational Theory positions ‘affect’ as a central issue to individual and collective disposition in constituting the affective political discourse, this paper will also indicate some political imperatives by advancing a politics of hope in the realm of socio-political sphere.     

The rise of Trump and an agenda for regulatory reform

The arrival of Trump in the White House does not augur well for the long-run prospects of the US economy. The protectionism that is gathering steam under his presidency may yield some short-term gains, but at the detriment of the long-run. Examining the discontent among ordinary voters that brought Trump to power, this paper argues that this should be treated as an opportunity for a major regulatory reform. With the advance of digital technology, we have increasing returns to scale, and that, in turn, is making our antitrust laws backfire and hurt the well-being of ordinary people, thereby sowing discontent. The paper builds a simple model to illustrate this and makes the case for revoking the older antitrust laws and replacing them with some simple profit-sharing rules at the level of the firm, and the economy.     

Scoring rule voting games and dominance solvability

This article studies the dominance solvability (by iterated deletion of weakly dominated strategies) of general scoring rule voting games when there are three alternatives. The scoring rules we study include Plurality rule, Approval voting, Borda rule, and Relative Utilitarianism. We provide sufficient conditions for dominance solvability of general scoring rule voting games. The sufficient conditions that we provide for dominance solvability are in terms of one statistic of the game: sufficient agreement on the best alternative or on the worst alternative. We also show that the solutions coincide with the set of Condorcet Winners whenever the sufficient conditions for dominance solvability are satisfied. Approval Voting performs the best in terms of our criteria.